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Logz.io’s cloud-native SaaS platform seamlessly scales with the cloud workloads and telemetry data volumes of Fortune 100 companies. You’ll have constant visibility into the health and performance of your infrastructure and applications without any effort needed to scale your observability infrastructure.
Observability starts with telemetry data – including logs, metrics, and traces – which contain insights into the current state of your databases (along with the rest of your stack). For this reason, the first step to gaining database observability is often collecting this data and storing it for analysis in an observability platform.
However, observability goes beyond collecting this data. Database observability should quickly answer questions like, what caused this sudden jump in latency? Or why are my databases consuming more infrastructure resources over time?
For this reason, it’s important to correlate signals from your database with other related components, such as the infrastructure that powers your database, or your applications that send requests to your database. Consider diving into full stack observability best practices to learn more.
Consider starting with the four golden signals for cloud monitoring, which include latency, traffic (which may be considered ‘throughput’ in database language), saturation (which measures infrastructure usage), and error rates. The four golden signals are industry standards for ensuring the reliability of modern cloud components.
Many get started with database monitoring before implementing full observability. Dive deeper into the four golden signals here.
Database observability has become increasingly expensive as digital traffic increases and cloud environments become larger, which both create larger telemetry data volumes.
The best way to reduce these costs is by minimizing the computing footprint of large data volumes via data optimization. By implementing data optimization techniques that eliminate useless data and reduce the cost of storage, engineering teams can reduce observability costs by 30-50%. Check out Logz.io’s automated data optimization capabilities here.
For those interested in basic database monitoring, the best options are open source tools, which include Prometheus, OpenTelemetry, Telegraph, Grafana, Fluentd, FluentBit, and OpenSearch for logs. They’re free and provide everything needed to surface new latency, monitor throughput, and collect other essential database observability metrics.
However, for those who need to troubleshoot and diagnose database performance problems as well, they’ll need an observability platform to unify and correlate the data. At Logz.io, we pride ourselves on being the most cost effective path to full database observability, but there are plenty of other options, including Datadog, Dynatrace, and New Relic.