The client is a company providing access to media content with a core audience in Europe and the USA. The company used a substantial and complex infrastructure consisting of bare-metal servers and virtual nodes in multiple data centers across Europe and Canada. The main problem regularly encountered by the client was the inability to determine with high confidence whether the entire infrastructure was functioning correctly. It was also extremely difficult to identify the cause of identified disruptions in the information systems, leading to many hours of manual analysis.

One of the key problems we identified immediately during the audit was an ineffective monitoring system with very limited capabilities for retrospective analysis.
We conducted several interviews with company representatives to gather as much data as possible on which business indicators were most important to the client. We also conducted a full audit of the entire infrastructure and identified the most vulnerable sections of the architecture.
We ranked all potential system failure scenarios by criticality, describing all metrics in code. Detailed documentation was also prepared for the client’s employees. In addition, we integrated Datadog with the existing emergency notification system used by the client. As a result, we ensured a seamless transition from the old monitoring system to the new one.

All key metrics were highlighted in separate, user-friendly dashboards, which were also described in terraform and deployed automatically. Thanks to this, the client’s engineers could access information about the system status at any time, grouped by functional groups. This significantly reduced the time needed to establish the cause of a failure.
In the next implementation phase, we developed response plans and DRPs for all key systems in the client's infrastructure. Each alert was automatically linked to the corresponding section of the documentation and contained comprehensive information on the actions of the on-duty personnel in an emergency.

In addition to typical, purely infrastructure indicators, we developed custom metrics that covered the client's business logic. For example, we monitored average profit indicators, and probe nodes simulated user behavior, assessing critical streaming quality and content availability metrics.
Everything was fully described in code and handed over to the client along with the documentation. Thanks to a significant improvement in monitoring quality, we managed to increase service availability to 99.8% and identify several hidden issues that were unknown before implementation.