Challenges
Self - Service
SRE/DevOps, dev teams, and other stakeholders need visibility into the behavior of applications they build and manage, and need to be able to find relevant telemetry quickly based on several search criteria to troubleshoot or optimize their applications
Always-on
Application telemetry (Traces, metrics, and logs) generated provides visibility and need a place to be stored on a continuous basis in your Observability platform
Variable Workload
Query workload is widely variable. Usually, the system receives relatively low query volume. However, when something goes wrong, there may be multiple teams querying telemetry simultaneously.
Cost
Cost of the observability platform impacts the bottom line of your application revenues and must be as low as possible
Solution
Standard Tooling
Standard tools like Kibana/Open Search Dashboards work natively with Mach5, allowing errors to surface quickly and be triaged, minimizing downtime
Auto-scaling
The system auto-scales according to changing query workloads, minimizing compute costs
Cost-effective Storage
Mach5 ingests and indexes logs and stores it in cost effective cloud storage in an extremely compressed form (up to 20x compression)
Availability
Separation of compute and storage increases reliability to make sure that your Observability platform stays up and responsive when you need it most
Benefits
Reduced TCO
10X cheaper than using Elasticsearch or OpenSearch for observability
System Reliability
Fully self managing compute and uses cloud storage for durability
Auto - scaling
Auto - scaling to minimize operational cost in the cloud
