View Excel templates directly in your browser. Click tabs to switch templates, sub-tabs for sheets. Each template also has a download link. Word documents are listed below for download.
| Common Migration Scenarios & Tools (Reference) | |||||||||
| Target Type | Target | Scenario | Migration Tool | Solution Overview | Applicable Scope | Notes | |||
| Cloud Host | CVM | VM online migration (no downtime) | go2tencentcloud | Online migration from source to Tencent Cloud without downtime; copies system params | IT cloud adoption; hybrid cloud; cross-cloud; cross-account/region | Requires COS-supported region; OS: CentOS/Ubuntu/Debian/Windows | |||
| Cloud Host | CVM | VM offline migration via image | Service Migration (MSP) | Migrates OS/apps/data via image (qcow2/vhd/vmdk/raw) to CVM/CBS | Image import for offline VMs | MBR only (no GPT/EFI); needs Virtio + cloud-init; destination disk >= source | |||
| Cloud Storage | COS | Object storage migration (fully-managed) | MSP Platform | Public network mode, no Agent needed, auto-executes | No Direct Connect available | Note: archived data must be restored to standard first | |||
| Cloud Storage | COS | Object storage migration (semi-managed) | MSP Platform | Deploy Agent on source; Agent pulls via intranet, pushes to COS | Direct Connect already established | Agent must access both source and Tencent COS via intranet | |||
| Cloud Storage | CFS | File storage migration | rclone | Sync between filesystems, directories, cloud storage | 70+ cloud storage products supported | Does not copy directory metadata; use rsync if metadata required | |||
| Database | MySQL | DB migration (full + incremental) | DTS | Supports MySQL/MariaDB/Percona/TDSQL-C/PostgreSQL/Redis/MongoDB/SQL Server | Self-built or other-cloud DB to Tencent Cloud | No distributed transactions; no STATEMENT binlog; no binlog clearing; no DDL during full; no user/port changes | |||
| Database | Redis | Redis migration to CRedis | DTS | Full + incremental sync; standard<->cluster supported | Redis 2.8-6.0; target >= source version | Requires SYNC/PSYNC permission; Aliyun 2.8 doesn't support → use redis-shake | |||
| Database | Redis | Source Redis without PSYNC permission | redis-shake | Export RDB from source; redis-shake reads and writes to Tencent Redis | Redis 2.8-7.2 | https://tair-opensource.github.io/RedisShake | |||
| Database | MongoDB | MongoDB to Tencent MongoDB | DTS | Full + incremental migration via DTS | All MongoDB versions | Must create read-only account on source instance | |||
| Database | SQL Server | Aliyun PaaS SQL Server to self-built | Aliyun DTS | Buy temp ECS on Aliyun, forward port 1433 to Tencent CVM; use Aliyun DTS with Tencent as target | Aliyun RDS SQL Server | Port forwarding workaround | |||
| Container | TKE | K8s cluster migration | Velero | Open-source backup/restore for k8s cluster resources & persistent volumes | Self-built or other-cloud k8s to TKE | Velero 1.5+ with Restic (--use-restic); no CRUD during migration; keep cluster specs similar | |||
| Middleware | Ckafka | Kafka migration | MirrorMaker / Dual-consume | 3 options: single-write dual-consume (simple); single-write single-consume (some backlog); MirrorMaker (syncs history) | All Kafka versions | Choose per scenario; MirrorMaker needs idempotent consumption | |||
| Middleware | RabbitMQ | RabbitMQ migration | Migration-to-Cloud | Migrate metadata via Tencent's migration-to-cloud platform | Open-source/other-cloud RabbitMQ | ||||
| Middleware | RocketMQ | RocketMQ to TDMQ | RocketMQ Migration-to-Cloud | Two modes: Perceptible (metadata import/export + switch); Imperceptible (zero-downtime cluster migration) | Self-built/other-cloud RocketMQ | Imperceptible mode supports pause/rollback | |||
| Middleware | Elasticsearch | ES data migration | COS Snapshot / ES_Migration | Snapshot-based migration for large data; ES_Migration tool for Aliyun ES | ES 5.x-7.x | Needs object storage + ES AKSK permissions on both ends | |||
| Middleware | CLS | Log service migration (Aliyun SLS → CLS) | MSP | For business migrating from Aliyun, logs also need migration | Aliyun SLS |
| o | Legend： | Planned | Finished | Ongoing | Delayed | Blocked | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Workstream | Overall Progress | 0.01 | Current Stage：Preparation | Schedule | M0 | M1 | M2 | M3 | M4 | M5 | M6 | M7 | M8 | M9 | M10 | M11 | M12 | ||||||||||||||||||||||||||||||||||||||||||||||||
| Stage | Task | Desc | progress | Status | Customer | Tencent | Tools | Start Time | Finish Time | May 2024 | W1 | W2 | W3 | W4 | W1 | W2 | W3 | W4 | W1 | W2 | W3 | W4 | W1 | W2 | W3 | W4 | W1 | W2 | W3 | W4 | W1 | W2 | W3 | W4 | W1 | W2 | W3 | W4 | W1 | W2 | W3 | W4 | W1 | W2 | W3 | W4 | W1 | W2 | W3 | W4 | W1 | W2 | W3 | W4 | W1 | W2 | W3 | W4 | W1 | W2 | W3 | W4 | |||
| Workload | Stage1： Prepare | Information Collection | Cloud Product Information Collection | Billing information collection | ongoing | SKU usage bills("actual cost" column deleted) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Product & Resource Infomation Collection | Resource information collection | not started | SKU usage bills("actual cost" column deleted) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Cloud products / components information collection | not started | Read Only Account | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Performance / Monitorning metrics collection | not started | Read Only Account | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Sign Contract | Sign the contract, Migration kickoff | not started | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Tencent Account | Tencent Cloud account preparation | not started | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Training on Tencent Cloud Products | Tencent Product & Service | Compute (CVM) | not started | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Storage (CBS, COS, CFS, etc.) | not started | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Network (VPC, CLB, CCN, VPN, etc) | not started | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Big Data (Wedata, EMR, DLC, etc) | not started | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Containers (TKE, TCR, etc) | not started | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Middleware (KMS, Database, MQ, TSF, etc) | not started | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Security (CFW, EdgeOne, ) | not started | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Terraform (Tencent Cloud Provider) | not started | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Stage2： Design | Business Architecture Research | Migration Solution Design | Business module research | not started | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Business dependency mapping | not started | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Resource usage analysis for each business module | not started | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Business SLA collection | not started | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Network Solution Design | Network | Network topology research | not started | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Network ACL research | not started | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Tencent Cloud network design (VPC / VPC Peer, etc.) | not started | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Designing the dedicated line solution during migration | not started | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Dedicated line construction | not started | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Product Feature Proof of Concept (PoC) Testing & Validation | Tencent Product & Service | Compute (CVM) | not started | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Storage (CBS, COS, CFS, etc.) | not started | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Network (VPC, CLB, CCN, VPN, etc) | not started | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Containers (TKE, TCR, etc) | not started | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Middleware (Database, MessageQueue, etc) | not started | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Terraform (Tencent Cloud Provider) | not started | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Reference Micro-service Example | not started | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Service Migration Plan & Solution Design | For each APPs & Platform & Engineering Platform | Overall Migration Plan | not started | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Detail Code adaptation and compatibility solution & plan | not started | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Detail Detail Deployment solution & plan | not started | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Detail Data migration solution & plan | not started | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Detail Service testing solution & plan | not started | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Detail Drill solution & plan | not started | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Detail Rollback solution & plan | not started | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Detail Cut-over solution & plan | not started | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Stage3： Implementation | DevOps platform | Terraform platform integration | Integrate with Tencent Cloud Terraform | not started | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| CI/CD/Internal tools/etc. | adaptation with Tencent Cloud | not started | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Infra Deployment | IAM Deployment | Account/privileage/tag/lable deployment | not started | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Monitoring& alert deployment | Deploy monitoring and alert system | not started | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| billing system Integration | Billing system integration with tencent cloud | not started | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Securty deployment | VM/WAF/security deployment | not started | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Audit sytem deployment | Auidt log | not started | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| VPC/Subnet deployment | VPC/Subnet deployment | not started | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Service Deployment & Migration for each Apps & Platforms | Tencent product & service adapataion | Object storage SDK | not started | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| APIs & Tencent product adapation | not started | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Object storage migration | migrate object storage to COS | not started | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| File storage migration | Migrate file storage to CFS | not started | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| service deployment | Deploy service on Tencent cloud | not started | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| database migration | Migrate database（redis/pg） | not started | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| business function test | Function test | not started | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| business load test | Load test | not started | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| service HA test | HA test on tencent | not started | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| cutover tool develpment | Prepare cutover tool and scripts | not started | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| prepare cutover runbook | Cutover runbook | not started | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| prepare rollback runbook | Rollback runbook | not started | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| first cutover dry-run | cutover dry-run and runbook elaborate | not started | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| second cutover dry-run | cutover dry-runr and runbook elaborate | not started | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| third cutover dry-run | cutover dry-run and runbook elaborate | not started | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| switch CVM to new AZ | switch cvm from 2AZ model to 3AZ model after 3rd AZ in operation | not started | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Stage4： Cutover | First Batch Cutover | non-production enviroment | dev environment uat environment | not started | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Second Batch Cutover (Platform & services which is independent ) | not started | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Third Batch Cutover (Platform & services which is independent ) | not started | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| … | not started | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Stage 5：summary & feature improvement | Observation | Observe service stability | not started | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Optimaztion | performance optimazation | not started |
| Tencent Cloud Application Cloud Migration Survey Outline | |||||||||||||||||||||||
| We will have surveys and interviews with the application owner, architecture, core engineer, etc., in order to find out the basic situation of the application, infrastructure, development and deployment details, the current running status, and provid... | |||||||||||||||||||||||
| Basic Information | |||||||||||||||||||||||
| Name | |||||||||||||||||||||||
| Business Domain | |||||||||||||||||||||||
| Business Description | Sample of Deployment Architecture Diagram | ||||||||||||||||||||||
| Application Owner | Contact Information (Email / Slack / IM…) | This generally refers to the deployment architecture of the application, which includes the distribution of resources in the cloud and their interrelationships, mainly at the infrastructure level. | |||||||||||||||||||||
| Architecture / Tech Lead | Contact Information (Email / Slack / IM…) | ||||||||||||||||||||||
| Developer / Vendor | Contact Information (Email / Slack / IM…) | Responsible for the code changes | |||||||||||||||||||||
| Q&A / Vendor | Contact Information (Email / Slack / IM…) | Responsible for the application function and performance verification | |||||||||||||||||||||
| OPS / Vendor | Contact Information (Email / Slack / IM…) | Responsible for the deployment and infrastructure changes | |||||||||||||||||||||
| Infrastructure Survery | |||||||||||||||||||||||
| ENV | how many running environments of this application, like: dev / uat / canary / prod-tl or prod-sh | ||||||||||||||||||||||
| ENV | we will collect the infra resources by enviroments. | ||||||||||||||||||||||
| Computing Resources | |||||||||||||||||||||||
| VM | Lists the virtual machines (AWS EC2, Alibaba ECS and the other VMs) in the current environment, with type size, storage, region and azs. | ||||||||||||||||||||||
| Container | If this app is deployed in container env, like k8s or docker-compose, list the container resources of all pods. | ||||||||||||||||||||||
| Function Computing | If this app is running in AWS lambda or the other FC runtime, list the function instances. | ||||||||||||||||||||||
| Others | For the other computing resources, list the details, for example bare metal servers or GPU clusters. | ||||||||||||||||||||||
| Persistence | |||||||||||||||||||||||
| RDBMS | List the instances of Relational Databases, like RDS MySQL, PostgreSQL and rest. | ||||||||||||||||||||||
| NoSQL | The NoSQL databases, like MongoDB, DynamoDB and others. | ||||||||||||||||||||||
| NewSQL | NewSQL databases, like TiDB, CockroachDB, TDSQL-C and others. | ||||||||||||||||||||||
| Object Storage | S3, OSS, MinIO and the other S3 like object storage. | ||||||||||||||||||||||
| File Storage | File system like NAS, Cloud FileSystem and rests. | ||||||||||||||||||||||
| Others | The on-prem databases like Oracle, DB2 and the other important systems around persistence instances, like AWS Athena | ||||||||||||||||||||||
| BigData | |||||||||||||||||||||||
| ADB | Analytical databases, BigQuery, SonwFlake, Redshift and rest. | Sample of Business Architecture Diagram | |||||||||||||||||||||
| Warehouse & Lake | Doris, Clickhouse, Teradata, EMR, MaxCompute and rest. | A business architecture diagram typically represents the business logic, particularly the dependencies of the application, upstream and downstream systems, etc. | |||||||||||||||||||||
| Data Development | The development tool or framework for data processing of this application | ||||||||||||||||||||||
| Others | Other important resourecs in bigdata domain of this application. | ||||||||||||||||||||||
| Middleware | |||||||||||||||||||||||
| MessageQueue | Message queue like Rocket MQ, AMQ and SQS. | ||||||||||||||||||||||
| Pub/Sub | System for Pub/Sub of this application, like Kafka, AWS Kinesis and rest. | ||||||||||||||||||||||
| Others | Any systems for asynchronous invocation and decoupling. | ||||||||||||||||||||||
| Network | |||||||||||||||||||||||
| VPC and Subnets | Like the network structure of this app, including VPC, Subnet and Network ACL if required. | ||||||||||||||||||||||
| LB and Gateway | Collect the Load Balancer / Gateway / Ingress. | ||||||||||||||||||||||
| Domain Names | The public / private domain names of this app, the DNS service provider. | ||||||||||||||||||||||
| CDN | The CDN usage of the application, accelerated domain names and objects, etc. | ||||||||||||||||||||||
| Others | Other important network components, such as VPNS, private lines or SDWAN, etc. | ||||||||||||||||||||||
| Security | |||||||||||||||||||||||
| WAF | Collect the WAF usage, including access mode, bandwidth, protection mode, access mode, etc. | ||||||||||||||||||||||
| Firewall | Cloud firewall or the on prem firewall (PaloAlto) for this application. | ||||||||||||||||||||||
| Security Groups and NACL | List the SG of this applications, and network access control list if exists. | ||||||||||||||||||||||
| Bastion | Sort out the usage of jump servers of bastion. | ||||||||||||||||||||||
| Data Security | The data security requirement, and KMS for example. | ||||||||||||||||||||||
| SSL certificates | The certs of this app. | ||||||||||||||||||||||
| The other security resources (HSM, security devices etc.) | |||||||||||||||||||||||
| Monitoring | |||||||||||||||||||||||
| Healthcheck | How the health of the application is checked, and whether there is a dashboard for monitoring. | ||||||||||||||||||||||
| APM | Details of the application performance monitoring, how to integrate and monitoring. | ||||||||||||||||||||||
| Logging | Log system. | ||||||||||||||||||||||
| Mertics & Alerting | This application's monitoring metrics and alarm methods. | ||||||||||||||||||||||
| Application Architecture Survey | |||||||||||||||||||||||
| Tech Stack | |||||||||||||||||||||||
| Programming Language | |||||||||||||||||||||||
| Frameworks and Libraries | |||||||||||||||||||||||
| Frontend Technologies | |||||||||||||||||||||||
| Backend Technologies | |||||||||||||||||||||||
| DevOps Tools | |||||||||||||||||||||||
| External APIs / SDK | |||||||||||||||||||||||
| Application Dependencies | |||||||||||||||||||||||
| Application Name | Endpoint | Interactive Method (Sync/Async 1:1/1:N) | Business relationship statement | ||||||||||||||||||||
| Application Name | Endpoint | Interactive Method (Sync/Async 1:1/1:N) | Business relationship statement | ||||||||||||||||||||
| Application Name | Endpoint | Interactive Method (Sync/Async 1:1/1:N) | Business relationship statement | ||||||||||||||||||||
| ... | |||||||||||||||||||||||
| Codebase | |||||||||||||||||||||||
| SourceCode Repo | |||||||||||||||||||||||
| IaC Code and others | |||||||||||||||||||||||
| DevOps | |||||||||||||||||||||||
| CI/CD Pipeline | |||||||||||||||||||||||
| IaC Implementation | |||||||||||||||||||||||
| Configuration | |||||||||||||||||||||||
| Performance Metrics | |||||||||||||||||||||||
| Q&A Methods | Investigate the application's testing methods, unit testing, functional testing, and performance testing. | ||||||||||||||||||||||
| RTO/RPO | |||||||||||||||||||||||
| Maximum Acceptable Downtime | Collect these cirtical metrics in disaster recovery and business continuty planning will help us set clear about the recovery time and data loss, for the potential distruptions. | ||||||||||||||||||||||
| Recovery Time Objective (RTO) | |||||||||||||||||||||||
| Recovery Point Objective (RPO) | |||||||||||||||||||||||
| Security & Compliance | |||||||||||||||||||||||
| Security Principle Learning | Understand existing security policies and compliance requirements. The entire migration process must comply with the customer's security and compliance requirements. | ||||||||||||||||||||||
| Data Security Requirement | Learn the organization's data security principle and requirements of this app, such as mandatory factors such as GDPR, PII. | ||||||||||||||||||||||
| Migration Processing Security | Evaluate security risks during migration and formulate corresponding security policies and measures to ensure migration security. | ||||||||||||||||||||||
| Technical Team Survey | |||||||||||||||||||||||
| Technical Team Session | Understand the capabilities and experience of the existing technical team. Assess the level of support from the team during the cloud migration process. | ||||||||||||||||||||||
| Tecent Cloud Training | Identify the potential involvement and training requirements from Tencent's side during the migration process. | ||||||||||||||||||||||
| Migration Plan: Landing Zone, Cloud Architecture (Resource and Costing), Migration Plan Details | |||||||||||||||||||||||
| Landing Zone Design | Based on Tencent Landing Zone best practice, Design a Landing Zone for the application's cloud migration, including networking, identity, security, monitoring, logging, etc. | ||||||||||||||||||||||
| Resource Planning and Costing | Analyze the cost components during the migration process, including cloud, software, migration manpower, and time costs, and develop a reasonable cost budget and optimization strategy. | ||||||||||||||||||||||
| Previous Migration Group Description | Describe the migration group of this application: Lift and Shift, Partial Migration, Re-Design & Migrate | ||||||||||||||||||||||
| Previous Migration Plan | Details of the previous migration plan and questions. | ||||||||||||||||||||||
| Previous Migration Compatibility | |||||||||||||||||||||||
| Previous Priority | |||||||||||||||||||||||
| Open Questions | |||||||||||||||||||||||
| 1. 4+1 architecture diagram, we should have deployment view and logic view for this app. | |||||||||||||||||||||||
| 2. Challenges of this application in the current business scenario | |||||||||||||||||||||||
| 3. Do we have document of 1 pager to contain the details of this app? | |||||||||||||||||||||||
| 4. For this app, why the previous migration plan wasn't executed? |
| No. | Process | Description | Completion Criteria |
| 1 | Project preparation | Party A proposes service requirements to Party B, and the Parties identify the key personnel involved as well as the requirements, necessary preparations, processes, arrangements, etc. | Party B sets up an implementation team, and confirms that the onsite conditions for implementation have been satisfied. |
| 2 | Research and assessment | Party B collects information on the application architecture, deployment architecture, technology stack, software and hardware dependencies, resource utilization, and other aspects of the cloud-based system. Party A assesses the risks and strategies ... | Party B submits the "Customer Business System Information Research Report" and the "Customer Business System Cloud Migration Assessment Report". Both parties have reached an agreement on the contents of the reports. |
| 3 | Development of cloud migration solutions | Party B will develop a detailed plan for migrating the system to the cloud, including strategies, contingency plans, resource planning, and progress tracking. | Both parties confirm the "Customer Business System Cloud Migration Technical Plan" and the "Customer Business System Cloud Migration Plan" and reach a consensus on the implementation details. |
| 4 | Environment preparation | Party B assists Party A to prepare cloud product resources required to migrate the application to the cloud, including CVM, cloud database and cloud storage. | |
| 5 | Migration testing | Party A performs migration testing for storage, databases, middleware, and applications, as well as cutover testing in the development environment. | |
| 6 | Migration | Party A performs the migration of databases, middleware, and applications in the production environment. | |
| 7 | Performance testing | Party A's application R&D team conducts functional and performance testing on the application. | |
| 8 | System cutover | Once the testing is successfully completed, the traffic will be redirected to the new system. | "Acceptance Report on Customer Business Systems Migration" |
| 9 | Stabilization | 5 days stable operation post-cutover. Monitor system availability, business metrics, HA. TSA inspection for optimization. | No cloud-caused incidents (15 calendar days) |
| 10 | Service acceptance | After 5 days of stable operation following the system cutover,Party B prepares the service acceptance materials and documentation. | Party B submits the " Acceptance Report on Customer Business Systems Migration", and Party A signs the report to confirm the acceptance. |
| Stage | # | Tasks | Client | Tencent | R | Responsible | The person or team who actually does the work to complete the task. They are the "doer" and are responsible for getting the job done. | ||
| Prepare | 1 | Migration scope definition | R | S | A | Accountable | The person ultimately answerable for the correct and thorough completion of the task. This person delegates the work and is the one who signs off on the final deliverable. Golden Rule | ||
| 2 | Provide resource inspection tools | S | R | C | Consulted | Those whose opinions are sought. They provide subject-matter expertise or advice and engage in two-way communication to shape the work. | |||
| 3 | Resource inspection(OR Tencent can do it with RO account provided) | R | S | I | Informed | Those who are kept up-to-date on progress, typically after a task is completed. Communication with this group is one-way. | |||
| 4 | Business inspection | R | S | ||||||
| 5 | Performance metric identification | R | S | ||||||
| Design | 1 | Business architecture research | S | R | |||||
| 2 | Cloud migration readiness check report | S | R | ||||||
| 3 | Cloud migration readiness check report review and approval | R | S | ||||||
| 4 | Network topology solution | S | R | ||||||
| 5 | LandingZone design(optional) | S | R | ||||||
| 6 | Business Architecture Design | R | S | ||||||
| 7 | Migration solution design and review | R | S | ||||||
| 8 | Migration Plan & WBS | R | S | ||||||
| 9 | Product Feature Proof of Concept (PoC) Testing & Validation | R | S | ||||||
| 10 | All products training | S | R | ||||||
| 11 | DevOps platform adaptation(Tencent can provide Terraform adaptation) | R | S | ||||||
| 12 | Cloud resources provision | S | R | ||||||
| Implementation | 1 | Cloud foundation/Devops platform deployment | R | S | |||||
| 2 | Business platform/Application Infra setup | R | S | ||||||
| 3 | Migration for each Apps & Platforms | R | S | ||||||
| 4 | Business scenario testing | R | S | ||||||
| 5 | Canary release cutover runbook and rollback preparation | R | S | ||||||
| 6 | Data sync automation & tooling (object storage/image/etc.) | R | S | ||||||
| 7 | Scale out application workload to the production size | R | S | ||||||
| 8 | Monitoring platform setup | R | S | ||||||
| 9 | Canary release drill | R | S | ||||||
| 10 | Business stress testing | R | S | ||||||
| 11 | Risk scan (optional) | S | R | ||||||
| Cutover | 1 | Tencent escort support group setup | S | R | |||||
| 2 | Canary release running | R | S | ||||||
| 3 | Application cutover | R | S | ||||||
| Summary & Improvement | 1 | Application stability observation | R | S | |||||
| 2 | Application performance optimization | R | S | ||||||
| 3 | Application HA improvement | R | S | ||||||
| 4 | Disaster recovery drill | R | S | ||||||
| 5 | Migration review and summary | S | R | ||||||
| Legend: | |||||||||
| R = Responsible | |||||||||
| S = Support | |||||||||
| - = N/A |
| The following image is a sample; please replace it with the actual architecture diagram for your business. | |||||||||||||
| Application Architecture Diagram | Integration Architecture Diagram | Operations Diagram | |||||||||||
| The Application Architecture Diagram illustrates the overall application landscape, including major systems, service components, and their interdependencies. It is used to identify migration scope, application coupling, and sequencing considerations ... | The Integration Architecture Diagram shows how internal and external systems interact through APIs, middleware, messaging platforms, batch jobs, or third-party interfaces. It helps identify integration dependencies, interface transformation requireme... | The Operations Diagram illustrates the operational management framework, like resource provision, monitoring, logging, alerting, and high-availability mechanisms. It is used to assess operational readiness, service resilience, and business continuity... | |||||||||||
| #VALUE! | #VALUE! | #VALUE! | |||||||||||
| Deployment Architecture Diagram | Network Architecture Diagram | Data Architecture Diagram | |||||||||||
| The Deployment Architecture Diagram shows how applications, middleware, and infrastructure components are deployed across different environments, such as data centers, virtual machines, containers, or cloud PaaS. It provides the foundation for resour... | The Network Architecture Diagram describes the end-to-end network topology, including VPCs, subnets, routing, firewalls, load balancers, connectivity links, and traffic paths. It is used to evaluate network dependencies, connectivity requirements, la... | The Data Architecture Diagram presents the core data domains, database platforms, storage systems, and data flow relationships across the environment. It is essential for assessing data migration complexity, synchronization requirements, data consist... | |||||||||||
| #VALUE! | #VALUE! | #VALUE! |
| Domain | |||
| No | Domain Name | Business | DNS Service Provider |
| 1 | xxx.com | app-1 | |
| 2 | xxx.com | ||
| 3 | xxx.com |
| Project VM Collection | 腾讯云对标(腾讯侧填写) | |||||||||||||||||||||
| No | Business | Region | AZ | Product Name | Product Type | OS Image | System Disk Type | Data Disk Type | CPU(vCPUs) | MEM(GiB) | System Disk(GB) | Data Disk(GB) | QTY | 产品名 | 产品型号 | 操作系统版本 | 磁盘类型 | CPU(core) | MEM(GB) | DISK(GB) | 台数 | 备注 |
| 1 | test | singapore | ap-signapore-1 | EC2 | t3.medium | Linux 8.4 | Enhanced SSD | Enhanced SSD | 2 | 4 | 50 | 100 | 1 | CVM | S5 | TencentOS | 普通云盘 | |||||
| 2 |
| No | Busienss | Region | Product Name | Standard Storage(GB) | Archive Storage(GB) |
| 1 | Singapore | OSS(Object Storage) | |||
| 2 | Singapore | NAS | |||
| 3 | Singapore | CFS (File System) |
| No | Cloud Vendor | Region | AZ | VPC ID | VPC CIDR | VPC Subnet ID | VPC Subnet CIDR | Business | Note |
| 1 | GCP | Silicon Valley | us-east-2a | vpc-xxx | 10.0.0.0/16 | subnet-xxx | 10.0.1.0/24 | ||
| 2 | GCP | Singapore | sg-southeast-1a | vpc-xxx | 172.16.0.0/16 | vsw-xxx | 172.16.1.0/16 |
| vpc | Security | Policy | Protocol | Port range | Source IP CIDR | Description |
| xxxx | xxxx | Accept | TCP | 1 | 0.0.0.0/0 |
| No | Business | Product Name | Region | AZ | Instance ID | Protocol | Business | Note | |||
| 1 | app-1 | ELB | tokyo | ap-tokyo-1 | xxx | Layer7/layer4 | test | ||||
| Database Information Collection | 腾讯云对标(腾讯侧填写) | ||||||||||||||||||||||||
| No | Env | Business | Product Name | Region | AZ | Version | Cross-AZ | Instance Type | Replicas | Disk Type | CPU(vCores) | MEM(GiB) | Storage(GB) | QTY | 数据库产品名 | 实例名称 | 实例版本 | 实例类型 | 是否跨区部署 | 部署架构 | CPU(vCPUs) | MEM(GiB) | Storage(GB) | 实例数 | Note |
| 1 | prod/test/dev | app-1 | mysql | Singapore | ap-signapore-1 | 5.7 | yes | general | 1 master/1 replica | Enhanced SSD | 2 | 4 | 50 | 1 | TencentDB for MySQL | 独享型 | |||||||||
| 2 | prod/test/dev | app-1 | redis | Singapore | ap-signapore-1 | 4 | no | standard | 1 master/2 replicas | - | - | 4 | - | 1 | Cloud Native Database TDSQL-C | 通用型 | |||||||||
| 3 | prod/test/dev | app-1 | redis | Singapore | ap-signapore-1 | 4 | no | cluster | 3 shards, 1master/1replica/shard | - | - | 12 | - | 1 | couting memory size of all shards | ||||||||||
| 3 | prod/test/dev | app-2 | mongodb | Singapore | ap-signapore-1 | 4.4 | no | replicaset | 1master/2 replicas | Enhanced SSD | 2 | 4 | 50 | 1 | TencentDB for Redis | 标准架构 | |||||||||
| 4 | prod/test/dev | app-2 | mongodb | Singapore | ap-signapore-1 | 4.4 | no | sharded | 3 shards, 1master/2replicas/shard | Enhanced SSD | 6 | 12 | 150 | 1 | TencentDB for Redis | 标准架构 | couting cpu and memory size of all shards |
| No | Business | Product Name | Instance ID | Spec(core) | Version | Note | |
| 1 | app-1 | GKE | xxx |
| No | Business | Product Name | Instance Name | Version | Spec | Bandwidth | Peak QPS | Cross-az | Note |
| 1 | app-1 | Kafka | xxx | 2.8.1 | 2c4g, 3 nodes | 100MB/s | Read：30w qps Write: 20w qps | yes | |
| 2 | app-1 | RabbitMQ | no | ||||||
| 3 |
| Security Product Names in GCP | Qty | |||||||
| Security product information collection demo as below: | ||||||||
| DDOS | ||||||||
| Instance ID | Packages | Basic Bandwidth(Gbps) | Elastic bandwidth(Gbps) | Business Bandwidth(Mbps) | QPS | Protected Domains | Protected Ports | Protected websites |
| WAF | ||||||||
| Region | Version | Protected Domains | Domain List | Other | ||||
| Mainland china | Advance | 1 | xx.com | |||||
| Bastion Host | ||||||||
| Region | Instance Qty | |||||||
| Product: | BigQUery | couting memory size of all shards | |||||||||||||||||||||||
| Type | Questions | Answers | Note | ||||||||||||||||||||||
| Architecture | What's the business architecture about BigQuery in GCP? | ||||||||||||||||||||||||
| What's the data upstream and downstream processes of BigQuery? | |||||||||||||||||||||||||
| which types of data source for BigQuery are, such as database, ETL, or other data sources? | |||||||||||||||||||||||||
| Which types of business application are using BigQuery? | |||||||||||||||||||||||||
| How the business accesses BigQuery data, by SQL or by API? | |||||||||||||||||||||||||
| What are the time requirements for data ingestion, such as T+1, hour-level, minute-level, or second-level? | |||||||||||||||||||||||||
| What are the time requirements for data query, such as T+1, hour-level, minute-level, or second-level? | |||||||||||||||||||||||||
| Usage Scenarios | What's the amount of daily incremental data for BigQuery? | ||||||||||||||||||||||||
| How many tables does BigQuery have ? | |||||||||||||||||||||||||
| How big is the largest table of BigQuery? | |||||||||||||||||||||||||
| How many fields does the largest table have? | |||||||||||||||||||||||||
| Whether the BigQuery has the dimension hierarchies, is there a documented methodology for this design? | |||||||||||||||||||||||||
| Whether the BigQuery uses Cloud Function, Cloud Scheduler, or other task scheduler tools (e.g, Aireflow) to migrate data and clean data, what's the number of Cloud Function, Cloud Scheduler API and Airflow task, and how about the scheduling period? | |||||||||||||||||||||||||
| Does BigQuery use stored procedure, how many approximate stored procedures ? | |||||||||||||||||||||||||
| What's the primary query type of BigQuery, how about the approximate rate? Such as aggregated query of one table, joined query of multi-table, primary key query | |||||||||||||||||||||||||
| What're the usage scenarios of datasets? |
| WeData(Tencent data integration, development, and governance platform) POC Requirement Collection Checklist | ||||||||||||||||||
| Please complete the "Customer Response" column for each item. Description/Options are provided for reference. | ||||||||||||||||||
| # | Section | Item | Description / Options | Customer Response | Notes | |||||||||||||
| 1. Customer Basic Information | ||||||||||||||||||
| 1 | 1. Customer Basic Information | Customer Name | Full company name | |||||||||||||||
| 2 | 1. Customer Basic Information | Customer Region / Location | Country/region, city, data center location | |||||||||||||||
| 3 | 1. Customer Basic Information | Team Size | Number of developers / data engineers who will use WeData | |||||||||||||||
| 4 | 1. Customer Basic Information | Migration Timeline | Expected POC duration and go-live date | |||||||||||||||
| 5 | 1. Customer Basic Information | Parallel Operation Requirement | Whether existing system needs to run in parallel during POC | |||||||||||||||
| 6 | 1. Customer Basic Information | Training Needs | Whether product training / workshops are required | |||||||||||||||
| 2. Data Ingestion Layer | ||||||||||||||||||
| 7 | 2. Data Ingestion Layer | T0 Layer Data Source Types & Versions | MySQL / PostgreSQL / Oracle / SQL Server / MongoDB / Kafka / API, with version numbers | |||||||||||||||
| 8 | 2. Data Ingestion Layer | Data Volume | Daily incremental volume, total data volume, peak TPS | |||||||||||||||
| 9 | 2. Data Ingestion Layer | Ingestion Method | Real-time (CDC / message queue), batch (full / incremental pull), hybrid | |||||||||||||||
| 10 | 2. Data Ingestion Layer | Upsert Requirement | Append-only or merge-update by primary key | |||||||||||||||
| 11 | 2. Data Ingestion Layer | Latency Requirement | Real-time (seconds/minutes), near real-time (hourly), T+1 | |||||||||||||||
| 12 | Data Ingestion Layer | MongoDB Usage Scenario | Specific business scenario where MongoDB is used: data type stored, read/write pattern, downstream consumers, retention policy, and reason chosen over a relational store | |||||||||||||||
| 3. Orchestration Layer | ||||||||||||||||||
| 12 | 3. Orchestration Layer | Current Scheduling Framework | Airflow / Databricks / SageMaker / custom-built | |||||||||||||||
| 13 | 3. Orchestration Layer | DAG Scale | Daily task count, DAG complexity (max depth / node count) | |||||||||||||||
| 14 | 3. Orchestration Layer | Dependency Types | Time-triggered, event-triggered, cross-DAG dependencies, sensors | |||||||||||||||
| 15 | 3. Orchestration Layer | Cross-Timezone Scheduling | How multi-region teams handle timezone differences | |||||||||||||||
| 16 | 3. Orchestration Layer | SLA & Alerting Requirements | Task timeout / failure alerting, alert channels (Email / Slack / Teams) | |||||||||||||||
| 17 | Orchestration Layer | Custom Scheduler – Base Framework | If the scheduling framework is custom-built, which open-source framework is it built on (e.g., Airflow, Celery, Luigi, Prefect, Dagster)? | |||||||||||||||
| 18 | Orchestration Layer | Total DAG / Job Count | Total number of scheduled DAGs / jobs currently running in production (daily / weekly / ad-hoc breakdown if available) | |||||||||||||||
| 19 | Orchestration Layer | Event Trigger Source | Which system or signal triggers event-based jobs? e.g., S3 file arrival (via SNS / SQS / EventBridge), Kafka topic, API webhook, DB change event | |||||||||||||||
| 4. ETL/ELT Development Layer | ||||||||||||||||||
| 17 | 4. ETL/ELT Development Layer | Current ETL Framework | dbt / Spark / Flink / custom framework / stored procedures | |||||||||||||||
| 18 | 4. ETL/ELT Development Layer | Development Language | SQL / Python / Scala / Java / other | |||||||||||||||
| 19 | 4. ETL/ELT Development Layer | Development Tool / IDE | Notebook (Jupyter / Databricks) / VS Code / Web IDE / other | |||||||||||||||
| 20 | 4. ETL/ELT Development Layer | Jar Package Tasks | Spark Jar / MapReduce Jar / custom Jar - quantity and management | |||||||||||||||
| 21 | 4. ETL/ELT Development Layer | Shell / Script Tasks | Bash scripts, Python scripts, or other non-SQL tasks | |||||||||||||||
| 22 | ETL/ELT Development Layer | Custom ETL Framework – Language & Base | Is the custom ETL framework written in Python? Which open-source framework(s) is it built on (e.g., PySpark, pandas, Dagster, Bonobo, Luigi)? | |||||||||||||||
| 5. Compute Engine Layer | ||||||||||||||||||
| 22 | 5. Compute Engine Layer | Current Compute Engine | Databricks / Snowflake / BigQuery / Spark / Trino / Presto / Hive | |||||||||||||||
| 23 | 5. Compute Engine Layer | Engine Version | Specific version number, any custom patches | |||||||||||||||
| 24 | 5. Compute Engine Layer | Resource Model | Serverless / fixed cluster / auto-scaling | |||||||||||||||
| 25 | 5. Compute Engine Layer | Concurrency & Performance Needs | Concurrent query count, typical query response time | |||||||||||||||
| 6. Machine Learning & AI | ||||||||||||||||||
| 26 | 6. Machine Learning & AI | ML Framework | MLflow / Kubeflow / SageMaker / custom platform | |||||||||||||||
| 27 | 6. Machine Learning & AI | Algorithm Types | Traditional ML (XGBoost/LightGBM/sklearn) / Deep Learning (PyTorch/TF) / LLM | |||||||||||||||
| 28 | 6. Machine Learning & AI | Training Infrastructure | GPU type / quantity, distributed training requirements | |||||||||||||||
| 29 | 6. Machine Learning & AI | Inference Deployment | Online (REST API) / offline batch / streaming inference | |||||||||||||||
| 30 | 6. Machine Learning & AI | Model Management | Model versioning, model registry, A/B testing | |||||||||||||||
| 31 | 6. Machine Learning & AI | Feature Store | Whether using Feature Store (Feast / Databricks / custom) | |||||||||||||||
| 32 | Machine Learning & AI | GPU Usage Scenarios | Detailed scenarios that require GPU (e.g., LLM fine-tuning, deep-learning training, embedding generation, batch inference). Expected GPU type, quantity, and utilization pattern | |||||||||||||||
| 7. Data Governance & Metadata | ||||||||||||||||||
| 32 | 7. Data Governance & Metadata | Metadata Management | Catalog (Unity Catalog / Hive Metastore / Atlas / DataHub) | |||||||||||||||
| 33 | 7. Data Governance & Metadata | Data Lineage | Data lineage tracking requirements, current implementation | |||||||||||||||
| 34 | 7. Data Governance & Metadata | Data Quality Monitoring | Great Expectations / dbt tests / custom rules / none | |||||||||||||||
| 35 | 7. Data Governance & Metadata | Data Classification | Data classification labels (PII / sensitive data tagging) | |||||||||||||||
| 36 | 7. Data Governance & Metadata | Data Access Control | Row-level / column-level permissions, dynamic masking | |||||||||||||||
| Data Governance & Metadata | Custom DQ & Classification – Language & Base | Which language is the custom Data Quality Monitoring and Data Classification framework written in (Python / Scala / Java / other)? Any underlying open-source library used (e.g., Great Expectations, Deequ, custom)? | ||||||||||||||||
| 8. Data Egress & Consumption | ||||||||||||||||||
| 37 | 8. Data Egress & Consumption | Egress Targets | MySQL / PostgreSQL / Doris / ClickHouse / ES / Redis / API / BI | |||||||||||||||
| 38 | 8. Data Egress & Consumption | Egress Method | Batch push / real-time sync / client pull | |||||||||||||||
| 39 | 8. Data Egress & Consumption | Downstream BI / Reporting Tools | Tableau / Power BI / Looker / Superset / custom | |||||||||||||||
| Data Egress & Consumption | Redshift Capacity Profile | Redshift total resources (node type & count, vCPU / core count, average and peak utilization), total job count, peak concurrency, and execution time of the most complex / longest-running job | ||||||||||||||||
| 9. Security & Integration | ||||||||||||||||||
| 40 | 9. Security & Integration | Regional Compliance Requirements | GDPR / SOC2 / ISO27001 / PDPA / local regulations | |||||||||||||||
| 41 | 9. Security & Integration | SSO Login Method | SAML / OAuth2 / OIDC / LDAP / AD / custom | |||||||||||||||
| 42 | 9. Security & Integration | Identity Provider | Okta / Azure AD / Google Workspace / self-hosted IDP | |||||||||||||||
| 43 | 9. Security & Integration | RBAC Requirements | Role/permission hierarchy, project/workspace isolation | |||||||||||||||
| 44 | 9. Security & Integration | Network Security Requirements | VPC peering / VPN / dedicated line / IP whitelist | |||||||||||||||
| 10. CI/CD & DevOps | ||||||||||||||||||
| 45 | 10. CI/CD & DevOps | Code Management Tool | GitHub / GitLab / Bitbucket / Azure DevOps | |||||||||||||||
| 46 | 10. CI/CD & DevOps | CI/CD Tool | GitHub Actions / GitLab CI / other | |||||||||||||||
| 47 | 10. CI/CD & DevOps | Environment Management | Dev / test / prod isolation, multi-env release process | |||||||||||||||
| 48 | 10. CI/CD & DevOps | Release Strategy | Blue-green / canary / direct release | |||||||||||||||
| 11. Data Pipeline Operations & Observability | ||||||||||||||||||
| 49 | 11. Data Pipeline Operations & Observability | Monitoring Solution | Grafana / DataDog / CloudWatch / custom | |||||||||||||||
| 50 | 11. Data Pipeline Operations & Observability | Alert Channels | Email / Slack / Teams / PagerDuty / WeChat Work / SMS |
| DLC (Data Lake Compute) POC Requirement Collection Checklist | ||||||
| Please complete the "Customer Response" and "Additional Notes" columns for each item. | ||||||
| # | Category | Item | Priority | Description | Customer Response | Additional Notes |
| Basic Information | ||||||
| 1 | Basic Information | Volume of existing data | Total storage size, growth rate | |||
| 2 | Basic Information | Format of existing data | File formats, encoding | |||
| 3 | Basic Information | Network/isolation and security requirements | VPC isolation, compliance needs | |||
| 4 | Basic Information | Data compression format | Snappy, Gzip, Zstd, etc. | |||
| 5 | Basic Information | Current storage bandwidth utilization | Peak/avg throughput | |||
| 6 | Basic Information | Current resource usage | CPU, memory, storage utilization | |||
| 7 | Basic Information | Current resource elasticity / scaling approach | Auto-scaling, manual, serverless | |||
| 8 | Basic Information | Competing vendor products currently in use | AWS/GCP/Azure services | |||
| Data Format | ||||||
| 9 | Data Format | Table types | Internal/external, managed/unmanaged | |||
| 10 | Data Format | Number of tables | Total table count | |||
| 11 | Data Format | Storage format (Parquet, ORC); lake format (Iceberg, Paimon, Hudi) | ||||
| 12 | Data Format | Primary key requirement | Yes/No, key columns | |||
| 13 | Data Format | Number of storage files and average file size | ||||
| 14 | Data Format | Hot/cold tiering, lifecycle management, or time travel | Retention policy, tiering rules | |||
| Data Ingestion / Egress | ||||||
| 15 | Data Ingestion / Egress | Data ingress/egress method | DataInLong / Stream / CLI / API / Other | |||
| 16 | Data Ingestion / Egress | Latency requirements for data writes | Real-time / near-real-time / batch | |||
| 17 | Data Ingestion / Egress | Data ingestion sources | e.g. MySQL CDC, Kafka, S3 | |||
| 18 | Data Ingestion / Egress | Data egress destinations | e.g. MySQL, Doris, BI tools | |||
| 19 | Data Ingestion / Egress | Daily incremental / updated data volume | GB/day | |||
| 20 | Data Ingestion / Egress | Upsert or append-only | Merge-update by key or append | |||
| Compute | ||||||
| 21 | Compute | Data types | Structured / semi-structured / unstructured | |||
| 22 | Compute | External system support | External tables, federation queries | |||
| 23 | Compute | Data governance / management requirements | Lineage, catalog, quality | |||
| 24 | Compute | Data security | Encryption, masking, RBAC | |||
| 25 | Compute | Functions | UDFs, stored procedures, built-in functions | |||
| 26 | Compute | Stored procedures usage | Yes/No, quantity, complexity | |||
| 27 | Compute | Semantics | ACID, eventual consistency | |||
| 28 | Compute | Workloads | Batch / interactive / streaming | |||
| Data + AI | ||||||
| 29 | Data + AI | AI & ML training requirements | Frameworks, GPU needs, integration | |||
| 30 | Data + AI | Offline inference requirements | Batch prediction, model serving | |||
| Product Features | ||||||
| 31 | Product Features | Observability | Query history, resource monitoring | |||
| 32 | Product Features | Integration with third-party monitoring / alerting | Grafana, DataDog, PagerDuty | |||
| 33 | Product Features | Resource consumption pattern | Burst / steady / periodic | |||
| 34 | Product Features | Other heavily relied-upon product features | Specify | |||
| 35 | Product Features | Ecosystem integration | Spark, Flink, dbt, Airflow, etc. | |||
| Storage Requirements | ||||||
| 36 | Storage Requirements | Storage capacity | Total TB required | |||
| 37 | Storage Requirements | Required storage bandwidth | MB/s or GB/s | |||
| 38 | Storage Requirements | Required storage QPS | Operations per second | |||
| Business Data Architecture | ||||||
| Please attach or describe the current data architecture, including data sources, storage, processing engines, downstream consumers, etc. To be discussed | ||||||
| Identified Risks / Concerns | ||||||
| Please list any known risks or concerns related to the migration. | ||||||
| Key Capability Assessment | ||||||
| Are there any special features that need to be migrated, e.g. stored procedures? (To be filled in by the customer.) To be discussed | ||||||
| XXCutover Implementation Manual (cutover window 7-X 00:00--7-X 06:00) | |||||||||||||||||||||||||||||
| Steps | Action Items | Operator | Time Estimation (mins) | Time Window | Remark | ||||||||||||||||||||||||
| 1. Preconditions | 1.1 | Carry out cutover job notification (internal) or announcement (external) | 30mins | Internal time: Communication completed / External time: 06-29 Announcement | 1. This table is only for preliminary planning reference, please adjust or add or delete according to actual needs. 2. In the early stage of the task, please evaluate the data and time, such as how long the business can be interrupted and the maximum... | ||||||||||||||||||||||||
| 1.2 | release no daily changes | 5mins | Changes stopped 6-30 | ||||||||||||||||||||||||||
| 1.3 | Security policy check (business system, database security policy, whitelist, etc.) | All invocation and whitelist settings have been completed | |||||||||||||||||||||||||||
| 1.4 | DNS domain name resolution configuration check | The domain name list has sorted out the corresponding relationship before and after the cut has been reviewed | |||||||||||||||||||||||||||
| 1.5 | Tencent cloud side write test for business COS | 30mins | completed | ||||||||||||||||||||||||||
| 1.6 | Tencent cloud Solr cluster test | 1hour | completed | ||||||||||||||||||||||||||
| 1.7 | Non-real-time incremental data check - COS data synchronization check on Tencent Cloud | 20mins | Data sampling completed, no data inconsistencies | ||||||||||||||||||||||||||
| 1.8 | Non-real-time incremental data check - Solr cluster data check on Tencent Cloud | 20mins | completed | ||||||||||||||||||||||||||
| 1.9 | Live Incremental Data Check - Database Data Sync Delay Confirmation | 2mins | Check multiple times a day | ||||||||||||||||||||||||||
| 2.0 | Self-built Kafka cluster on Tencent Cloud | 120mins | completed | ||||||||||||||||||||||||||
| 2. Prepare | 2.1 | Close the Alibaba Cloud flow entry (close LB, external IP, etc., only keep the maintenance page or close all) | 5mins | 23:00 | /opt/ngxinx/sbin/nginx -s stop | ||||||||||||||||||||||||
| 2.2 | Stop the execution of all Alibaba Cloud tasks (pay attention to scheduled tasks) - The Web application layer service on the Alibaba Cloud side stops, and the writing to Cloud Storage stops. | 20mins | 23:05 | ||||||||||||||||||||||||||
| 2.3 | Stop the execution of all Alibaba Cloud tasks - Stop the XX cluster service on the Alibaba Cloud side | 10mins | 23:05 | ||||||||||||||||||||||||||
| 2.4 | Stop the execution of all tasks on the Alibaba Cloud side - All scheduled tasks of Alibaba Cloud cluster | 10mins | 23:15 | ||||||||||||||||||||||||||
| 2.5 | Stop other services or interfaces on the Alibaba Cloud side | 5mins | 23:05 | ||||||||||||||||||||||||||
| 2.6 | Stop the business alarm on the Alibaba Cloud side: close the alarm service, cmdb data synchronization and alarm registration service | No alarm yet | |||||||||||||||||||||||||||
| 3. Cutover | 3.1 | Alibaba Cloud MySQL is set to read-only and verified | 2mins | 23:25 | Adjust the database read_only parameter to ON show global variables like "%read_only%" verify view read_only | ||||||||||||||||||||||||
| 3.2 | Kill Alibaba Cloud MySQL tail connection | 3mins | 23:27 | Reference method: show processlist & kill id Note: Do not kill connections related to Binlog Dump | |||||||||||||||||||||||||
| 3.3 | Verify Alibaba Cloud MySQL and Tencent Cloud CDB data consistency, DBA or business sampling | 10mins | 23:40 | ||||||||||||||||||||||||||
| 3.4 | Delayed confirmation, the database synchronization task between Alibaba Cloud MySQL and Tencent Cloud CDB stops | 2mins | 23:50 | ||||||||||||||||||||||||||
| 3.5 | Set Tencent Cloud CDB as writable | 2mins | 23:52:00 | ||||||||||||||||||||||||||
| 3.6 | Change the database connection of the Tencent Cloud web application and write the data to the Tencent Cloud CDB | 5mins | 23:54:00 | Need business collaboration review | |||||||||||||||||||||||||
| 3.7 | Change the data volume of other operating systems to link to Tencent Cloud CDB | 5mins | 23:59:00 | ||||||||||||||||||||||||||
| 3.8 | Configuring COS back-to-origin on Tencent Cloud | 2mins | 24:04 | ||||||||||||||||||||||||||
| 3.9 | Alibaba Cloud stores tail data and prepares for incremental synchronization to Tencent Cloud COS | Synchronous execution, the incremental data is returned to the source through COS before the completion of the incremental data | |||||||||||||||||||||||||||
| 3.10 | Adjust Tencent cloud side business to write to Tencent cloud side Kafka cluster | 5mins | 23:59:00 | completed | |||||||||||||||||||||||||
| 3.11 | Check the startup status of each service component on the Tencent Cloud side (summary confirmation or split confirmation) | 30mins | 24:30 | Nginx Solr spider kafka tomcat | |||||||||||||||||||||||||
| 3.12 | Effective Alibaba Cloud side entry Forwarding pre-configured, ready to divert flow to the new environment on Tencent Cloud side. | 5mins | No need to jump | ||||||||||||||||||||||||||
| 3.13 | Tencent cloud-side key business rapid simulation test (hosts binding and other methods) | 30mins | 01:00:00 | ||||||||||||||||||||||||||
| 3.14 | Close maintenance page | 5mins | Just switch the domain name | ||||||||||||||||||||||||||
| 3.15 | Configure DNS resolution to Tencent Cloud portal address | 5mins | 01:30:00 | Approximate effective time- 10 minutes | |||||||||||||||||||||||||
| 3.16 | Star the business portal to divert flow to Tencent Cloud | ||||||||||||||||||||||||||||
| 3.17 | Relevant teams test Tencent cloud side main link business | 30mins | 1:35 | The main service R&D is tested in the evening, and the business test has been informed to the test team to test in the morning | |||||||||||||||||||||||||
| 3.18 | Legacy Issues handling | ||||||||||||||||||||||||||||
| 4. Office DNS Switch | 4.1 | Clear the DNS cache of the office network network device (if there is no historical configuration, it will be ignored) | No intranet DNS | ||||||||||||||||||||||||||
| 4.2 | DNS resolution of the office network device to the new IP address (ignored if there is no historical configuration) | ||||||||||||||||||||||||||||
| 5. Inspection after cutover | 5.1 | Observation service operation | |||||||||||||||||||||||||||
| 5.2 | Observation data indicators | ||||||||||||||||||||||||||||
| 5.3 | Legacy Issues & Archives | ||||||||||||||||||||||||||||
| 6. Old Environment Clear | 6.1 | Retain the Alibaba Cloud environment for two weeks | |||||||||||||||||||||||||||
| 6.2 | Clear Alibaba Cloud environment | ||||||||||||||||||||||||||||
| ... (51 more rows — download for full data) | |||||||||||||||||||||||||||||
| XXCutover(Rollback) Implementation Manual (cutover window 7-X 00:00--7-X 06:00) | |||||||||||||||||||||||||||||
| Steps | Action Items | Operator | Time Estimation (mins) | Time Window | Remark | ||||||||||||||||||||||||
| Rollback | 1.1 | Alibaba Cloud MySQL is set to writable | 5mins | ||||||||||||||||||||||||||
| 1.2 | Restart Alibaba Cloud MySQL jobs： - Restart Web layers - Restart scheduled tasks - Restart other services | 30mins | |||||||||||||||||||||||||||
| 1.3 | Verify status of Alibaba Cloud services started | 10mins | |||||||||||||||||||||||||||
| 1.4 | Configure DNS resolution to Alibaba Cloud portal address | 10mins | |||||||||||||||||||||||||||
| 1.5 | Close maintenance notification page | 10mins | |||||||||||||||||||||||||||
| 1.6 | Relevant teams test business | 30mins | |||||||||||||||||||||||||||
| 1.7 | Start Alibaba Cloud side business alarm: enable alarm service, cmdb data synchronization and alarm registration service | ||||||||||||||||||||||||||||
| ... (16 more rows — download for full data) | |||||||||||||||||||||||||||||