Sherlock Calls
for Datadog + PostgreSQL
Datadog monitors every layer of your infrastructure with metrics and traces. PostgreSQL stores your application's core operational data and business records. When you need to investigate across both, the evidence is split between two dashboards neither of which knows the other exists. Sherlock Calls bridges them — no code, no exports, no manual joins. Ask once from Slack and get a sourced answer in under 5 seconds.
TL;DR — What beta users get access to
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Sherlock Calls connects to Datadog, PostgreSQL simultaneously — read-only, no code changes, no webhooks — and lets you query both with a single Slack message.
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Ask questions that neither Datadog nor PostgreSQL can answer alone. Datadog shows infrastructure events — not how they map to call failures or customer impact. PostgreSQL holds every business record your app has ever created — but turning that into an answer requires a developer to write the query. Sherlock deduces the complete picture from both.
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No dashboard switching, no manual joins, no fog of uncertainty — ask in Slack and receive a sourced answer with evidence from every connected provider in under 5 seconds. The game is afoot.
<5s
Answer to any observability + database query
2
Connected platforms, 1 Slack question
0
Code changes or webhooks required
The Investigation Gap
What's invisible when you use Datadog + PostgreSQL without Sherlock
Each platform shows you its own data. But the questions that matter most live in the gaps between them.
Slow Datadog queries and PostgreSQL infrastructure events are logged separately — but they're often the same incident
A Datadog query performance degradation can be both a cause and a symptom of PostgreSQL infrastructure events. Without correlating both timelines, post-mortems diagnose symptoms while the actual root cause hides in the other platform's logs.
PostgreSQL alerts fire without the Datadog context that explains their impact
PostgreSQL tells you an infrastructure service is degraded. Datadog holds the application records and event tables that show which users and processes were affected. The gap between "infrastructure health" and "business impact" requires evidence from both.
Datadog performance baselines and PostgreSQL capacity planning are disconnected
PostgreSQL scales infrastructure based on load metrics. Datadog query patterns and ingestion rates are the actual load drivers — but they're not in PostgreSQL's view. The result: over-provisioning in the wrong areas and degradation where Datadog load actually concentrates.
Cross-Provider Questions
What teams ask Sherlock about Datadog + PostgreSQL
Questions that would take hours to answer manually — answered in under 5 seconds from Slack.
- SC“Which Datadog slow queries in the last 24 hours correlate with PostgreSQL infrastructure alerts?”
- SC“Show me PostgreSQL incidents where the root cause was a Datadog query performance degradation”
- SC“What's the Datadog query volume pattern before and after each PostgreSQL deployment this week?”
- SC“Find PostgreSQL alerting events that preceded Datadog database lock or timeout incidents”
- SC“Which Datadog tables show the highest read load during PostgreSQL high-traffic incidents?”
Beta Setup
Connect Datadog + PostgreSQL to Sherlock in 2 minutes
No code, no webhooks, no new dashboards. Beta users get direct onboarding support.
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Connect Datadog
Add your Datadog credentials to Sherlock Calls. Read-only access — no code changes, no webhooks, no Datadog configuration required.
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Connect PostgreSQL
Add your PostgreSQL credentials. Sherlock indexes all relational tables, business records, operational data, and application state automatically.
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Ask your first cross-provider question. The game is afoot.
Type any question about your combined Datadog + PostgreSQL stack in Slack. Sherlock queries all connected platforms in parallel, correlates the evidence, and returns a sourced answer in under 5 seconds.
FAQ
Common questions about Sherlock + Datadog + PostgreSQL
How does Sherlock Calls connect Datadog and PostgreSQL data?
- Sherlock uses read-only API access to both platforms simultaneously. When you ask a question, it queries Datadog, PostgreSQL in parallel, correlates the results by timestamp and shared identifiers, and produces a single sourced answer — the same way a good detective correlates evidence from multiple witnesses.
Do I need to set up any data pipelines between Datadog and PostgreSQL?
- No. Sherlock Calls is entirely pull-based — it queries both APIs on demand when you ask a question. There are no webhooks, no ETL pipelines, no data warehouses, and no code changes required in any of the connected platforms.
What kinds of questions can I ask about my Datadog + PostgreSQL stack?
- You can investigate anything that spans both platforms — alert rate, latency, and service health, table row counts and query latency, cross-platform costs, handoff patterns, and performance comparisons. Sherlock translates your plain-English question into the right API calls and returns the deduced answer.
Is my Datadog and PostgreSQL data stored by Sherlock?
- No. Sherlock Calls queries your data in real time and returns results directly to Slack — nothing is stored, indexed, or replicated in any Sherlock database. All data remains in Datadog and PostgreSQL and is accessed only during an active investigation.
How long does it take to set up the Datadog + PostgreSQL integration?
- Elementary — typically under 5 minutes total. Connect each platform with read-only credentials, install the Sherlock Calls Slack app, and ask your first question. No engineering, no dashboards, no onboarding calls required.
Apply for early access to Sherlock + Datadog + PostgreSQL
We're accepting a select group of beta users to shape the Datadog + PostgreSQL combination. Tell us about your stack and we'll reach out personally if you're a fit.
Explore individual integrations