Why MCM Observability
The problems with monitoring cloud infrastructure per provider and how MCM Observability solves them.
Why MCM Observability
Understanding what your cloud infrastructure is doing in real time — whether a workload is healthy, what its error rate is, how a request flows across services — requires pulling data from separate logging platforms and metrics dashboards, each scoped to a single provider. When something breaks at 2 AM, navigating between CloudWatch, Azure Monitor, and a separate APM tool to correlate a log entry with a latency spike is the problem, not the investigation itself.
Challenges & How MCM Solves Them
Each challenge below is a real friction point teams face when monitoring cloud workloads across providers without a unified layer.
1. Fragmented Monitoring Tools
CloudWatch handles AWS; Azure Monitor handles Azure; neither speaks to the other. Engineers switch between at least two consoles to answer "is anything broken right now?" — before they even touch application-level telemetry.
How MCM solves it: MCM Observability ingests logs and metrics from all connected providers into a single telemetry pipeline. One dashboard shows the health of your entire estate — no provider-hopping required.
2. Logs Are Siloed and Hard to Search
Log data is spread across CloudWatch Log Groups, Azure Log Analytics workspaces, and host syslog — each with its own query language, retention policy, and access model. Searching across all of them for a single event is impractical without a dedicated logging platform.
How MCM solves it: MCM centralises log collection across all connected accounts and providers. Logs from AWS, Azure, and Linux hosts land in the same index, searchable with a single query. No need to run parallel searches across separate tools.
3. No Cross-Cloud Metrics Correlation
A spike in Azure VM CPU, a rise in AWS Lambda error rate, and a queue depth increase across both are separate signals in separate tools. Correlating them to diagnose a cascading failure requires exporting data manually and comparing it side by side.
How MCM solves it: MCM Observability stores metrics from all providers in a normalised time-series format. You can overlay metrics from AWS and Azure resources on the same chart — no manual export or spreadsheet comparison.
4. Complicated Agent Setup
Getting logs and metrics off a server usually means a different agent, installer, and configuration for every Linux distribution.
How MCM solves it: MCM uses a standalone Elastic Agent with an installer that works across supported Linux distributions, with no separate fleet server to run. Hosts running Ubuntu, Debian, RHEL, CentOS, Amazon Linux, SUSE, Rocky Linux, AlmaLinux, or Oracle Linux can all be monitored the same way.
MCM vs Managing Observability Individually
| Aspect | Individual Provider Tools | MCM Observability |
|---|---|---|
| Log search | Per-provider query language, separate indexes | Unified log index, single search interface |
| Metrics | Separate dashboards per provider | Normalised time-series, cross-provider overlay |
| Agent install | Different agent per OS and provider | One standalone agent across Linux distributions |
| Incident correlation | Manual export and comparison | Correlated telemetry in one view |
| Host coverage | Cloud resources only | AWS, Azure, and Linux hosts |
Features
| Feature | Description |
|---|---|
| Centralised log collection | Ingest and search logs from AWS CloudWatch, Azure Monitor, and Linux hosts in a single index |
| Real-time metrics | Collect and visualise real-time and historical metrics for resources, costs, and platform health across all providers |
| Cross-provider metrics overlay | Plot AWS and Azure metrics on the same chart for direct comparison and correlation |
| Linux host monitoring | Logs and metrics for hosts across Ubuntu, Debian, RHEL, CentOS, Amazon Linux, SUSE, Rocky Linux, AlmaLinux, and Oracle Linux |
| Standalone Elastic Agent | One-step agent installation across Linux distributions, with no separate fleet server to run |
| Platform health metrics | Built-in metrics for MCM module job health — discovery runs, policy evaluations, cost ingestion — alongside infrastructure metrics |
| Retention and query | Configurable log and metrics retention with a query interface for ad-hoc investigation |
Why MCM Orchestration
The problems with provisioning cloud infrastructure per provider and how MCM Orchestration solves them.
MSP & Enterprise Home & Custom Dashboard
How MCM's ready-made dashboards, home page choice and custom dashboard builder give MSPs and Enterprise teams instant operational visibility.