8 Best All-in-One Observability Platforms for Logs, Metrics and Traces (2026)

The best all-in-one observability platform is the one that connects your logs, metrics and traces during an incident, supports the instrumentation you already run, and charges for the workload you actually have. Those are three different tests. A shared UI is nice, but it is not much consolation when you still have to copy a trace ID into another search box to find out why production is on fire.

This comparison covers eight useful candidates, not eight winners of a mysterious universal ranking. Start with Datadog for a broad product portfolio, Dynatrace or New Relic for a shared query layer, and Dash0 or SigNoz for an OpenTelemetry-native approach. Grafana Cloud suits Prometheus-oriented teams, Elastic offers deployment flexibility, and Coralogix gives you customer-owned archive storage. The right shortlist depends on what happens when you try to follow a failed request through all three signals.

Dash0 publishes this article and is included in the comparison. Each vendor gets the same profile template; product and pricing details come from public documentation checked in November 2026. No hands-on benchmark was run. The lists are editorial starting points, not measured performance rankings, so use your own telemetry to settle the details.

What makes an observability platform "all-in-one"

"All-in-one" should mean you can investigate one failure across logs, metrics and traces, not merely that the vendor has found room for three icons in the navigation. Check the architecture behind the claim:

1. Where do the signals live? Dynatrace (Grail), New Relic (NRDB), Elastic, SigNoz and Dash0 provide a shared data platform or layer for logs, metrics and traces. Grafana Cloud uses a separate backend per signal. Datadog sells each signal as a separate product with its own meter. Coralogix uses customer-owned object storage with separate archive configurations for metrics and for logs/traces; metrics also use a different query language. A common data layer can simplify cross-signal work. It cannot grant your query language capabilities it doesn't have.
2. What does OpenTelemetry actually unlock? The products here accept OTLP for logs, metrics and traces, but some have metric-type limitations or features that require their own agents. A successful export tells you that the backend received data. It doesn't tell you whether the feature you bought can use it.
3. Can you ask one question across signals? One query language can simplify an investigation, although support for joins and individual records still varies. Separate query languages can work just as well for navigational pivots, provided the identifiers and links are configured.

Then look at the billable unit. Hosts, GB, records, metric series, seats and credits all respond differently to the same deployment. A large log line matters to per-GB pricing; thousands of tiny log lines matter to per-record pricing. And the incident doesn't become cheaper merely because more engineers need access.

For the underlying concepts, see what observability means.

How these eight were selected

The eight profiles cover several genuinely different approaches to storing, querying and paying for telemetry. This is an editorial shortlist, not an exclusive list of qualified platforms. IBM Instana and Honeycomb also support relevant workflows and publish prices. They are not here because the comparison has a fixed scope, not because someone found a disqualifying flaw.

Every profile covers signal support, OTLP, query behavior, published pricing and deployment. The selection includes shared data layers, separate signal backends, OpenTelemetry-native products and self-hostable options. Order is editorial, not a numerical score. Other candidates are discussed below.

The eight platforms at a glance

1. Datadog

Datadog is a sensible place to look when you want infrastructure, APM, logs, RUM and security tools from one vendor. The catch is that "one vendor" does not mean "one billable unit." Several products come with their own meters, and you'll need to model the combination you actually use.

Signals and storage

Metrics, logs, APM traces, profiling, real user monitoring, session replay and synthetics live under one UI but are priced as distinct products. Each Datadog site (US, EU, Japan and others) is an independent backend, and data isn't shared between sites. Bits AI SRE is its incident investigation agent.

OpenTelemetry support

You can send OTLP through the DDOT Collector embedded in the Datadog Agent (the recommended path), an upstream OpenTelemetry Collector, the Agent's OTLP receiver or direct OTLP ingest. Coverage isn't uniform. According to Datadog's compatibility table, Continuous Profiler, App and API Protection, Data Streams Monitoring and Jobs Monitoring need the Datadog SDK. Live Processes, Universal Service Monitoring, Cloud Network Monitoring and Database Monitoring need the DDOT Collector. Running the OpenTelemetry Collector on EKS Fargate isn't supported and leads to incorrect host billing.

Metric mapping deserves its own trial. Datadog defines custom metrics partly by whether a metric maps to a supported integration. An OpenTelemetry metric that misses the no-cost mapping may become a billed custom metric. The data is exactly as useful as before; the meter has simply changed. Check mapping and cardinality with real payloads.

Querying

Each product has its own search syntax, and DDSQL offers a PostgreSQL-compatible subset across Datadog data. Prometheus compatibility is primarily ingestion-oriented; Datadog does not document PromQL as a native query interface.

Pricing

From the Datadog pricing list, annual billing, with headline prices marked "starting at":

• Infrastructure: Pro $15, Enterprise $23 per host per month.
• APM: from $31 per host per month.
• Logs: $0.10 per GB ingested, plus $1.06 to $2.50 per million indexed events depending on retention (3 to 30 days).
• Custom metrics: $5 per 100 indexed, with 100 per host included on Pro and 200 on Enterprise.
• Spans: $0.10 per GB ingested, plus $1.27 to $2.50 per million indexed spans.
• Managed Platform OTLP (direct OTLP ingest): $0.50 per GB of spans.
• Free tier: up to 5 hosts with 1-day metric retention.

Deployment

Primarily SaaS. Datadog also describes product-specific BYOC capabilities for logs; check the current product availability and supported environments rather than assuming its entire observability platform is self-hostable.

Limitations

The feature catalogue can be appealing. So can the bill, until you've remembered to include host fees, custom metrics, log indexing and span indexing. Which meter dominates depends on your workload. Some features still require Datadog-specific instrumentation even when your applications already emit OTLP.

Best for

Teams that want broad product coverage and are prepared to manage metric cardinality, indexed logs and span costs.

For a closer look at how the bill grows, see Datadog pricing explained.

2. Dynatrace

Dynatrace's argument is relatively easy to understand: let OneAgent discover your environment, bring the data into Grail, and ask questions with DQL. That removes a lot of setup work for enterprises that can adopt its agent and data model. It does not remove the need to understand what OTLP features the backend actually supports.

Signals and storage

The Grail data lakehouse stores logs, metrics, spans and events together. Real user monitoring, synthetics and application security are also available. Smartscape maps the topology of your environment, and Dynatrace Intelligence adds AI agents and an assistant.

OpenTelemetry support

Dynatrace accepts OTLP traces, metrics and logs through its OTLP API, an upstream Collector or the Dynatrace Collector. The main caveat is metrics: OTLP metrics must use delta temporality. Cumulative counters and histograms are not supported by the OTLP metrics mapping, so send delta temporality or validate a conversion step in your Collector pipeline. Delta exponential histograms map to gauges, with histogram buckets not ingested. The OneAgent remains the deepest integration. OpenTelemetry browser data, for example, doesn't get real user monitoring features such as sessions and Session Replay.

Querying

Dynatrace Query Language (DQL) works across all signals and supports joins, for example joining spans to logs on trace_id. The OneAgent adds trace and span IDs to logs automatically. There's no PromQL querying.

Pricing

From Dynatrace pricing, consumption-based:

• Full-Stack Monitoring: $58 per month per 8 GiB host. Infrastructure Monitoring: $29 per host per month.
• Logs: $0.20 per GiB ingested, plus retention and either per-query or bundled query pricing.
• Metrics: $0.15 per 100,000 data points. Traces: $0.20 per GiB.
• Retention: Grail metrics 15 months; trace retention starts at 10 days and is configurable; log retention can be set from 1 day to 10 years, with 10–35 days included under the bundled-query pricing option. See Dynatrace retention periods.
• 15-day free trial.

Deployment

SaaS on AWS, Azure and Google Cloud across many regions. Dynatrace Managed runs on-premises but doesn't include Grail.

Limitations

If your metrics pipeline sends cumulative counters, that is not an implementation detail you can ignore until the dashboard is blank. Validate delta conversion before rollout. Pricing also depends on host memory and data usage, while Dynatrace retains its own naming dictionary alongside OpenTelemetry conventions.

Best for

Large environments that want automatic topology and one query language over a single data store, and where the OneAgent is acceptable.

3. New Relic

New Relic puts telemetry in NRDB and uses NRQL across signals. That makes the query story straightforward. The pricing story has another character in it, though: the engineer who needs a full-platform seat. Teams with a small group of investigators may find that tradeoff perfectly reasonable.

Signals and storage

APM, infrastructure, logs, metrics, browser monitoring and synthetics all go into NRDB, New Relic's telemetry database. Its AI features include New Relic Autopilot, formerly SRE Agent.

OpenTelemetry support

New Relic accepts native OTLP for all three signals, with US, EU, Japan and FedRAMP endpoints. It recommends delta temporality for counters and histograms; cumulative works but increases ingest. The documented limits:

• 128 attributes per record.
• String values truncated at 4,095 characters.
• Complex attribute value types are generally pruned, with documented log-specific exceptions.
• A success response doesn't guarantee the data was ingested, so check for NrIntegrationError events.

Querying

New Relic Query Language (NRQL) works across all signals. A PromQL-style query mode is translated to NRQL. Because NRDB stores counters as deltas, functions like rate() can behave differently from Prometheus.

Pricing

From New Relic pricing:

• Free: 100 GB ingest per month and 1 full platform user.
• Ingest beyond that: $0.40 per GB, or $0.60 per GB with Data Plus. The EU region adds $0.05 per GB.
• Users: core users from $49 per month. Full platform users cost $99 each on the Standard plan (first user $10, maximum of five) and $349 each on Pro, billed annually.
• Default retention: traces 8 days, logs 30 days, aggregated metrics 13 months.

New Relic also lists a compute-based pricing model; evaluate it separately from the per-user figures above.

Deployment

SaaS only.

Limitations

A seat-based bill follows the number of engineers who need full access, not just the volume of telemetry. Also test existing PromQL habits against New Relic's delta-based storage model: familiar syntax is no guarantee of identical query semantics.

Best for

Teams that want a single ingest meter and have a small group of full platform users.

4. Dash0

Dash0 is for teams that would rather keep OpenTelemetry as the instrumentation contract. SignalStore handles the telemetry, PromQL covers stored metrics and on-demand aggregations over other signals, and SQL handles record-level investigation. That is a clearer division than pretending every query has to look like a metric. Pricing is usage-based rather than tied to host or user counts.

Signals and storage

Dash0 covers logs, metrics, traces, web events (real user monitoring), session replay, synthetic API checks and, since its August 2026 acquisition of Polar Signals, continuous profiling. Every signal type goes into SignalStore, a single OpenTelemetry-native data layer. Agent0, its set of AI agents, and an MCP server sit on top of that data.

OpenTelemetry support

Dash0 ingests OTLP for its supported telemetry signals without requiring a proprietary application agent. Its Kubernetes operator can manage supported auto-instrumentation paths; verify language and runtime coverage in your environment.

Querying

Dash0 uses synthetic metrics to aggregate logs, spans and web events through PromQL without materializing time series first. This supports counts, rates, durations, charts and alerting by attribute. It is not a raw-record PromQL join: individual logs, spans and web events can also be queried with SQL, or inspected through the correlated views. Synthetic metrics operate on the records retained after collection and sampling.

Pricing

From the Dash0 pricing page:

• Spans, logs and web events: $0.06 per million ingested plus $0.54 per million stored, with 30-day retention.
• Metric data points: $0.02 per million ingested plus $0.18 per million stored, with 13-month retention.
• Synthetic API check runs: $0.20 per thousand. Session replays: $2.00 per thousand.
• Agent0: $0.60 per credit.
• No per-user or per-host fees. There's a 14-day free trial with no credit card.

Volume-tiered ingestion pricing is available above 200 billion signals per signal type per month when you use SignalControl Edge, a component you run in your own network to filter and sample telemetry before it reaches Dash0.

Deployment

Storage and querying are hosted, with two US and two European storage regions listed in Dash0 documentation. SignalControl Edge runs in your network, but storage and querying stay in Dash0.

Limitations

There is no self-hosted query backend, BYOC deployment or air-gapped option. If one of those is mandatory, Dash0 is not your candidate. Otherwise, validate the integration catalogue, access controls and dashboard workflows against your needs rather than assuming OpenTelemetry-native means feature parity with every incumbent.

Best for

Teams committed to OpenTelemetry who want PromQL for metrics and synthetic aggregations, SQL for record-level work, and no host or seat fees.

5. Grafana Cloud

Grafana Cloud fits teams that already speak Prometheus and are comfortable connecting separate signal backends. Mimir, Loki and Tempo give metrics, logs and traces different engines and different query languages. The upside is flexibility. The price is configuration, especially when you want a trace and its logs to find each other.

Signals and storage

Each signal has its own backend: Mimir for metrics, Loki for logs, Tempo for traces and Pyroscope for profiles. Grafana dashboards and Explore connect them. Frontend Observability, synthetics, load testing and incident response are also available. In 2026 Grafana made Assistant Investigations, an agentic root-cause tool, and a Cloud MCP server generally available.

OpenTelemetry support

Grafana Cloud exposes a native OTLP endpoint for metrics, logs and traces. Grafana recommends Alloy, its own OpenTelemetry Collector distribution, for production. The upstream Collector works with extra setup.

Querying

Each signal has its own language: PromQL for metrics, LogQL for logs and TraceQL for traces. Cross-signal correlation happens through links between data sources in Grafana.

Pricing

From Grafana Cloud pricing:

• Free: 10,000 metric series, 50 GB each of logs, traces and profiles, 14-day retention and 3 users.
• Pro: $19 per month platform fee plus usage. Metrics from $6.50 per 1,000 series (13-month retention). Logs, traces and profiles at $0.05 per GB processed, $0.40 per GB written and $0.10 per GB retained (30 days). $8 per active user.
• Enterprise: from a $25,000 per year commitment.

Deployment

Grafana Cloud is available as managed SaaS or BYOC on supported clouds. Self-hosting the open-source Mimir, Loki, Tempo, Pyroscope and Grafana components is a separate deployment approach, not a self-hosted edition of Grafana Cloud.

Limitations

If you self-host the open-source components, you also own their upgrades and capacity. In Grafana Cloud, the operational work moves to configuring the data-source links and understanding several billing units. The backends cooperate very well once the labels agree. They are less helpful when the labels don't.

Best for

Prometheus-heavy teams that want an open-source path, BYOC or a large free tier.

6. Elastic Observability

Elastic is worth examining when logs already live in Elasticsearch or your infrastructure rules out a SaaS-only backend. Logs, metrics and traces use Elasticsearch data streams, with deployment choices ranging from Serverless to self-managed. The options are real, but so are the differences in features between them.

Signals and storage

Logs, metrics, traces, synthetics, real user monitoring and profiling are stored together in Elasticsearch. Elastic AI Agent handles chat-based investigation, and the 9.4 release added agentic Kubernetes investigation.

OpenTelemetry support

Elastic's Managed OTLP Endpoint takes logs, metrics and traces and stores them in the OpenTelemetry data model without translation. It's available on Elastic Cloud Serverless and, since March 2026, on Elastic Cloud Hosted (version 9.0 and later). It isn't available on self-managed deployments, which use Elastic's own OpenTelemetry distribution (EDOT) instead.

Querying

ES|QL is the main query language, with time-series support added in 9.4. KQL and Lucene are available for search. Native PromQL support was in technical preview in 9.4.

Pricing

From Elastic Serverless Observability pricing, "Complete" tier, prices marked "as low as":

• Ingest: $0.09 per GB for logs and traces, $0.023 per GB for metrics.
• Retention: $0.019 per GB-month, or $0.005 per GB-month for metrics.
• Egress: 50 GB free, then $0.05 per GB.

Elastic Cloud Hosted is priced by provisioned resources, and the self-managed distribution is free.

Deployment

Serverless on AWS, Google Cloud and Azure; Hosted across numerous AWS, Azure and Google Cloud regions; or self-managed.

Limitations

Don't assume a feature works merely because two Elastic deployments share a logo. Serverless still differs from Hosted: Elastic's comparison lists real user monitoring as planned, and Universal Profiling and APM tail-based sampling as unavailable. Self-managed Elasticsearch clusters require capacity planning, upgrades and storage operations; Serverless costs depend on actual ingest and retention.

Best for

Log-centric teams, and organizations that need self-managed or specific-region deployment.

7. Coralogix

Coralogix is a fit when keeping your telemetry archive in your own cloud account matters. It processes data as SaaS, then writes to customer-owned storage, with separate bucket configurations for metrics and logs/traces. You gain control of the archive, not a magic waiver from understanding the query pipelines.

Signals and storage

Coralogix covers logs, metrics, traces, APM, infrastructure monitoring, real user monitoring and security. Data is processed in-stream and written to customer-owned archive storage. Coralogix requires separate archive buckets for metrics and logs/traces; hot search behavior depends on the pipeline. Olly is its AI investigation agent.

OpenTelemetry support

Coralogix accepts OTLP over gRPC and HTTP for logs, metrics and traces, with a hard limit of 10 MB per request. Size Collector batches below that limit; Coralogix recommends smaller batches of around 2 MB.

Querying

There are two languages. DataPrime, a pipe-based language, queries logs and spans. Metrics are queried with PromQL in Metric Explorer, dashboards and alerts. Lucene is available for free-text log search.

Pricing

From Coralogix pricing, pay as you go:

• Logs: $0.42 per GB. Logs in the Frequent Search tier: $1.15 per GB.
• Traces: $0.16 per GB.
• Metrics: $0.06 per GB, where 1 GB equals 750 active time series.
• Unlimited users and hosts. 14-day trial.

Plans are sold in units against a daily quota. The daily quota renews each day, and Pay-As-You-Go can allow consumption up to twice the plan quota.

Deployment

Coralogix runs processing as SaaS while archive storage resides in customer-owned buckets, configured separately for metrics and logs/traces.

Limitations

Coralogix asks you to understand both the query language and the pipeline your data entered. That's worth checking with a real incident workflow: you can have a perfectly good trace, a perfectly good log archive, and no searchable log in the tier you're using when you click through.

Best for

Teams that want per-signal pricing, no user or host fees, and customer-owned archive storage with separate metrics/logs configurations.

8. SigNoz

SigNoz combines an OpenTelemetry-native ingestion path with ClickHouse storage, whether you use the managed service or operate it yourself. That appeals to teams that want a single application rather than assembling separate metrics, logs and trace backends.

Signals and storage

Logs, metrics, traces, exceptions and infrastructure monitoring share one store. Noz, an in-product AI assistant, and an MCP server were added in 2026.

OpenTelemetry support

SigNoz is built around OpenTelemetry and ingests OTLP for all three signals.

Querying

The Query Builder covers logs, traces and metrics. PromQL is available for metrics in dashboards and metric alerts, while ClickHouse SQL is available in dashboard queries.

Pricing

From SigNoz pricing:

• Teams: $49 per month, including $49 of usage.
• Logs and traces: $0.30 per GB, with 15-day retention.
• Metrics: $0.10 per million samples, with 1-month retention.
• No per-user or per-host fees. Enterprise starts at $4,000 per month.

Deployment

SigNoz Cloud, dedicated cloud, BYOC, self-hosted Enterprise or the free self-hosted Community edition.

Limitations

The Teams plan has relatively short default retention, and longer log retention needs a plan check. Self-hosting gives you control, along with the database maintenance. ClickHouse does not patch itself just because the observability interface is open source.

Best for

Teams that want OpenTelemetry-native observability with an open-source, self-hostable option.

Other platforms worth considering

The eight above aren't the entire market. In particular, these products are worth considering when their architecture or commercial terms match your requirements:

• IBM Instana supports logs, metrics and traces, including OpenTelemetry log ingestion, with published pricing. It appears to meet the original four screening checks. It is outside this eight-product editorial selection, not disqualified by them.
• Honeycomb offers an investigation-first experience for high-cardinality events, with generally available metrics and a Pro plan starting at $150 per month for 50 million events. It is another valid comparison candidate, not a platform that failed the screening checks.
• Splunk Observability Cloud historically used Log Observer Connect for logs stored in Splunk Platform. Since September 2026, Splunk also documents Observability Logs alongside metrics and traces, including OpenTelemetry onboarding. Evaluate the specific log offering and current package instead of assuming it is still only an external link.
• Sumo Logic publishes dollar list prices for its Cloud Flex Credits. Its pricing is credit-based, but it is not excluded for lacking public rates; evaluate its coverage and credit model on their merits.
• Cortex XCOR, built from Chronosphere after Palo Alto Networks completed its acquisition in January 2026, describes credit-based pricing without public numerical list rates. That makes like-for-like price modeling harder.
• OpenObserve offers an open-source approach to logs, metrics and traces. Include it when self-hosting or a single-binary deployment is a priority rather than excluding it for unmeasured popularity.
• Observe by Snowflake, acquired by Snowflake in 2026, is another option for teams already invested in that ecosystem. Its omission here reflects the article's scope, not a product verdict.
• ClickStack uses ClickHouse Cloud infrastructure and storage pricing rather than a separate event-based observability rate card. PromQL support was still documented as experimental in 2026, so test that path if it matters to you.

An eight-product article is a format choice. Your proof-of-concept shortlist has no reason to respect it.

How to choose an all-in-one observability platform

Choose by constraints first. Storage architecture and OTLP support matter, but the fastest way to shorten the shortlist is to identify the requirement a product cannot negotiate around.

Must the backend run in your environment? If data has to stay in your infrastructure, look at SigNoz, the open-source Grafana stack or self-managed Elastic. Grafana Cloud and SigNoz also offer BYOC. Dash0's storage/query backend and New Relic are SaaS; check Datadog's product-specific BYOC availability rather than assuming the entire platform can run in your account. Dynatrace Managed is distinct from the SaaS Grail experience. Coralogix processes telemetry as SaaS and stores its archives in customer-owned buckets.

What must work without a proprietary agent? If you want to instrument once and keep the option to switch vendors, check each platform's caveats against your pipeline. Dash0 and SigNoz are built around OTLP. Datadog and Dynatrace accept OTLP, but some features work best or only with their own agents. On Dynatrace, plan for delta metrics. For the wider OpenTelemetry tooling landscape, see the best OpenTelemetry tools.

Which query language do you want to standardize on? If your team writes PromQL today, Dash0 uses PromQL for metrics and derived aggregations from logs and spans, while Grafana Cloud, SigNoz and Coralogix use PromQL for metrics. Dynatrace (DQL), New Relic (NRQL) and Elastic (ES|QL) each offer one proprietary language across signals.

What does your workload make expensive? The relevant meter depends on the shape of your telemetry, not the headline price:

• With few, large hosts and moderate data volumes, Datadog's flat per-host price is easy to forecast. Dynatrace bills Full-Stack Monitoring per 8 GiB of host memory, so a large host counts as several units.
• With many verbose log lines, compare per-GB rates (Coralogix, Elastic, SigNoz, New Relic, Grafana Cloud).
• With many small records, per-record pricing (Dash0) behaves differently from per-GB pricing. To compare the two, measure your average record size: at an average encoded size of 1 kB and using decimal GB, 1 GB represents about 1 million records before compression and billing adjustments.
• If many engineers need full access, seat pricing (New Relic, Grafana Cloud) adds up. Dash0, Coralogix and SigNoz don't charge per user.

Run your real numbers through each shortlisted vendor's pricing page instead of comparing headline rates.

AI assistance is now common across these products. That makes the demo less interesting, not more. Give the assistant a failure with a known cause, check which telemetry it cites, and see whether its confident explanation survives contact with the evidence.

Once you have a shortlist, run a consistent proof of concept covering data fidelity, investigation outcomes, alert behavior and switching costs. The guide to choosing a platform without vendor lock-in covers how to check portability before you commit. If you're replacing one of these platforms, the alternatives guides for Datadog, Dynatrace, New Relic, Elastic, Coralogix and SigNoz go deeper.

FAQ

What is an observability platform?

An observability platform collects and analyzes telemetry, including logs, metrics and traces, to help explain system behavior. "All-in-one" usually means those signals are available through one product experience. It does not promise a single physical store, a universal query language or working cross-signal correlation without configuration.

What are the top observability platforms?

There is no universal winner. If you want OpenTelemetry-native instrumentation, start by evaluating Dash0 and SigNoz; for an existing Prometheus estate, consider Grafana Cloud; for a unified query layer, examine Dynatrace and New Relic. Datadog, Elastic and Coralogix have different strengths in coverage, deployment and storage. Use your incident workflow and costs to choose.

Is Grafana an observability platform?

Grafana on its own is a visualization tool. Grafana Cloud and the open-source LGTM stack (Loki, Grafana, Tempo, Mimir) together form an observability platform, with a separate backend for each signal.

Is Splunk an observability platform?

Yes. Splunk Observability Cloud covers metrics, traces, real user monitoring and synthetics. Its historical Log Observer Connect path reads logs stored in Splunk Platform; the newer Observability Logs offering also brings logs into the Observability Cloud experience. Check which package and collection path you are evaluating.

Final thoughts

Pick the platform that lets your team move from a symptom to the relevant request, logs and infrastructure without performing the correlation by hand. Then confirm that it accepts your actual OpenTelemetry data, runs where you need it and bills on units you can forecast. A platform can technically ingest all three signals and still make a terrible incident companion. The proof is the investigation, not the product label.

Use one failing request and one representative month of telemetry in your trial. Check the cross-signal path, the missing features and the bill before committing. For a broader market view, see the best observability tools. If an OpenTelemetry-native data layer and PromQL/SQL workflow fit your needs, try Dash0 free for 14 days. No credit card required.