Sherlock Calls
for ClickHouse + Datadog
ClickHouse stores and queries high-volume event and operational data at scale. Datadog monitors every layer of your infrastructure with metrics and traces. 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 ClickHouse, Datadog 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 ClickHouse nor Datadog can answer alone. ClickHouse holds the raw source of truth — but querying it for business questions requires SQL access and data engineering resources. Datadog shows infrastructure events — not how they map to call failures or customer impact. 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 database + observability query
2
Connected platforms, 1 Slack question
0
Code changes or webhooks required
The Investigation Gap
What's invisible when you use ClickHouse + Datadog without Sherlock
Each platform shows you its own data. But the questions that matter most live in the gaps between them.
Slow ClickHouse queries and Datadog infrastructure events are logged separately — but they're often the same incident
A ClickHouse query performance degradation can be both a cause and a symptom of Datadog infrastructure events. Without correlating both timelines, post-mortems diagnose symptoms while the actual root cause hides in the other platform's logs.
Datadog alerts fire without the ClickHouse context that explains their impact
Datadog tells you an infrastructure service is degraded. ClickHouse 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.
ClickHouse performance baselines and Datadog capacity planning are disconnected
Datadog scales infrastructure based on load metrics. ClickHouse query patterns and ingestion rates are the actual load drivers — but they're not in Datadog's view. The result: over-provisioning in the wrong areas and degradation where ClickHouse load actually concentrates.
Cross-Provider Questions
What teams ask Sherlock about ClickHouse + Datadog
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 ClickHouse infrastructure alerts?”
- SC“Show me ClickHouse incidents where the root cause was a Datadog query performance degradation”
- SC“What's the Datadog query volume pattern before and after each ClickHouse deployment this week?”
- SC“Find ClickHouse alerting events that preceded Datadog database lock or timeout incidents”
- SC“Which Datadog tables show the highest read load during ClickHouse high-traffic incidents?”
Beta Setup
Connect ClickHouse + Datadog to Sherlock in 2 minutes
No code, no webhooks, no new dashboards. Beta users get direct onboarding support.
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Connect ClickHouse
Add your ClickHouse credentials to Sherlock Calls. Read-only access — no code changes, no webhooks, no ClickHouse configuration required.
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Connect Datadog
Add your Datadog credentials. Sherlock indexes all infrastructure metrics, APM traces, logs, and alert events automatically.
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Ask your first cross-provider question. The game is afoot.
Type any question about your combined ClickHouse + Datadog 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 + ClickHouse + Datadog
How does Sherlock Calls connect ClickHouse and Datadog data?
- Sherlock uses read-only API access to both platforms simultaneously. When you ask a question, it queries ClickHouse, Datadog 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 ClickHouse and Datadog?
- 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 ClickHouse + Datadog stack?
- You can investigate anything that spans both platforms — query volume and event ingestion rate, alert rate, latency, and service health, 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 ClickHouse and Datadog 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 ClickHouse and Datadog and is accessed only during an active investigation.
How long does it take to set up the ClickHouse + Datadog 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 + ClickHouse + Datadog
We're accepting a select group of beta users to shape the ClickHouse + Datadog combination. Tell us about your stack and we'll reach out personally if you're a fit.
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