Datadog

Datadog is what most engineering teams quietly run their production on. Infrastructure, application performance, logs, real user data, security signals, all flowing into one platform. The technology side is solved. The part that breaks is what happens after a signal fires. That is the layer we build.

What Datadog Does

Datadog is a unified observability and security platform that ingests telemetry from your entire stack, hosts, containers, services, logs, browsers, and security tools, then makes that data searchable, correlatable, and alertable in one place. More than 800 turn-key integrations cover the major cloud providers, databases, and SaaS tools.

• Infrastructure Monitoring, host-level metrics, container visibility, Kubernetes observability, and network performance across hybrid and multi-cloud environments.
• APM and Distributed Tracing, service-level latency, error tracking, code profiling, and Universal Service Monitoring for services without manual instrumentation.
• Log Management, high-volume ingestion at $0.10 per GB, indexing by log event, Flex Storage for warm retention, and Sensitive Data Scanner for PII redaction.
• Real User Monitoring and Session Replay, browser and mobile telemetry that ties frontend performance to specific users and journeys.
• Synthetic Monitoring, scheduled API and browser checks from global locations to catch issues before real users do.
• Cloud Security suite, including Cloud SIEM, Cloud Security Posture Management, Vulnerability Management, and Code Security (SAST and SCA).
• Cloud Cost Management and LLM Observability, two newer products that map infrastructure spend and AI workload behavior into the same panes as your reliability data.

Datadog's AI: Watchdog and Bits AI

Watchdog is the embedded anomaly detection layer. It analyses billions of data points across metrics, traces, and logs and flags concerning patterns without configuration. Bits AI sits on top as the agentic layer, with Bits AI SRE for autonomous incident investigation and Bits AI Security Analyst for triaging security signals. Both work best when they have somewhere to push findings. Without routing into your incident workflow, ticketing system, or revenue dashboards, the AI just generates more notifications no one reads.

Automations We Build with Datadog

Datadog produces the signal. The automations we build decide who sees it, when, and what gets done about it. Every play below is something we have shipped or scoped for a mid-market team running real production traffic.

• Severity-aware alert routing into PagerDuty, Opsgenie, and Slack with deploy-window suppression so on-call only wakes up for genuine pages.
• Auto-ticketing from Watchdog anomalies and APM errors into Linear or Jira, with the affected service, deploy SHA, runbook link, and a starter root-cause summary attached.
• Cloud cost threshold alerts that fire to finance and engineering leads in Slack when a team or service crosses a daily or monthly spend ceiling.
• Weekly reliability digests pulled from SLO data, incident counts, and error budgets, sent to engineering leadership in a single email and pinned in a Slack canvas.
• LLM Observability hooks for AI features, alerting product owners when prompt failure rate, latency, or cost per request drifts outside a defined band.
• Revenue-aware dashboards that overlay Stripe events, signups from HubSpot or Salesforce, and product analytics on top of latency and error rate, so reliability conversations include the business impact.
• Incident retrospective workflows that pull timeline, related deploys, affected customers, and Datadog timeline links into a single Notion or ClickUp doc the moment an incident closes.

Why Teams Choose Datadog

• One platform for infrastructure, applications, logs, security, and cost. No stitching together three vendors and a homegrown Grafana stack.
• Watchdog and Bits AI surface real issues without manual threshold tuning, which matters more as service counts grow past what humans can dashboard.
• Native OpenTelemetry support and an API broad enough to drive almost any downstream automation, which is exactly where we plug in.
• Pricing scales by host and ingested volume, so mid-market teams can start narrow on what matters most (usually APM plus log management) and grow scope as the value lands.

Datadog Infrastructure Pro starts at $15 per host per month annual, APM at $31 per host per month with infrastructure, and Log Management ingestion at $0.10 per GB. Native integrations with AWS, GCP, Azure, Kubernetes, Stripe, Slack, PagerDuty, Linear, Jira, and roughly 800 others cover most stacks out of the box. The build we do sits on top of all of that, turning the raw observability into the operational and financial workflows your team actually runs.