Single service comparison

Azure Monitor Logs organizes telemetry in Log Analytics workspaces with Azure Resource Manager-managed RBAC, diagnostic settings, resource-centric data export, and Kusto Query Language (KQL). LTS organizes data in log groups and log streams, ingests via ICAgent/SPI/API, supports keyword and standard SQL query syntax (100+ SQL functions), and applies Huawei Identity and Access Management plus log-stream tags for tenancy. The query language and workspace topology are not portable between platforms without re-authoring queries and access grants.

Azure integrates natively with Azure Monitor metrics, alerts, workbooks, Logic Apps, Event Grid, and Sentinel for cross-resource correlation, with retention tiers and interactive/archived tiers governed per workspace. LTS integrates with AOM, APM, CES, CTS, OBS, DMS, and DWS for ingest, transfer, and long-term storage, exposing tiered cold/hot storage and SQL-based dashboards. Operational responsibility differs: Microsoft operates the workspace plane end-to-end while Huawei delivers LTS as a regional, pay-per-use managed service with region-scoped data residency and quotas.

Scaling and HA models diverge: Azure Monitor Logs is a globally available PaaS with committed ingestion throughput, workspace replication, and a 99.9% service-level objective backed by Microsoft's regional architecture. LTS offers a 99.95% SLA, claims ingestion of hundreds of TB per day, and fast scale-out, but data is regional, capacity is governed by Huawei per-region quotas, and cross-region/query federation is not equivalent to Azure's workspace-level resource graphs. Architects must verify per-region quotas, retention ceilings, and query concurrency limits before assuming parity.

Assessment and target choice: Inventory Azure Log Analytics workspaces, data sources (diagnostic settings, agents, Data Collection Rules), KQL queries, saved searches, workbooks, alert rules, and retention/archival tiers. Confirm LTS is the core equivalent for collection, search, and storage, but expect to add AOM for container/application O&M, APM for application metrics/traces, CES for resource metrics, and CTS for audit logs where Azure Monitor covered those domains. Map each workspace to LTS log groups/streams with matching tenant boundaries and IAM roles; reconcile region residency and retention requirements per Huawei region.

Data and configuration migration: There is no Microsoft-authored one-click Azure-to-LTS migration path. Re-export historical telemetry from workspaces via API or Log Analytics export to Azure Storage, then transfer to Huawei (for example, via OBS into LTS through supported transfer destinations such as OBS, DMS, and DWS) with the ephemeral pipeline you build. Re-author KQL as SQL or keyword searches, re-create structured parsing rules (regex, JSON, delimiters, Nginx, cloud-service templates), re-deploy alert rules as keyword/SQL alarms with SMS/email/DingTalk/WeCom/HTTP notifications, and re-deploy ICAgent on hosts to replace Azure Monitor Agent.

Application and integration migration: Replace Azure Monitor diagnostic settings and resource providers with LTS one-click ingest for supported Huawei Cloud services (ELB, VPC, APIG, CTS, WAF, OBS, and others) for native services, and rewire custom and cross-cloud logs through the LTS API/SDK. Re-implement downstream consumers — dashboards, runbooks, ticketing, and security analytics (Sentinel equivalents are not part of LTS; plan a separate SIEM or use CTS/CFW audit pipelines). Validate export schedules and re-route alert targets to Huawei notification endpoints before switching producers.

Validation, cutover, and gaps: Run dual ingestion in parallel to compare volume, latency, query results, and alert fidelity. Validate structured parsing parity, dashboard semantics, and audit-retention compliance (audit logs often require 180-day-plus retention, which LTS supports via OBS permanent storage). Recalculate TCO: Azure charges by ingested GB, retained GB, and query/alert execution; LTS charges by ingested volume, read/write, indexing, and storage with tiered cold/hot storage — estimate with peak load, retention period, and transfer traffic. Cutover per workspace once parity is proven, retaining read-only Azure workspaces during the agreed rollback window.