> ## Documentation Index
> Fetch the complete documentation index at: https://docs.devinenterprise.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Evaluate 30 Logging Libraries for Your Stack

export const UseCaseHero = ({title, description, prompt, category, features, devinUrl, agent, intent, playbookId, type}) => {
  const encodedPrompt = encodeURIComponent(prompt || '');
  const tag = 'docs-use-case-gallery';
  const utm = 'utm_source=docs&utm_medium=use-case-gallery&utm_campaign=hero-cta';
  const agentParams = (agent ? '&agent=' + agent : '') + (intent ? '&intent=' + intent : '') + (playbookId ? '&playbookId=' + playbookId : '');
  const devinHref = type === 'schedule' ? 'https://app.devin.ai/settings/schedules/create?' + utm + agentParams + (prompt ? '&prompt=' + encodedPrompt : '') : type === 'review' ? 'https://app.devin.ai/review?' + utm : agent === 'ada' ? 'https://app.devin.ai/search?' + utm + '&noSubmit=true' + (prompt ? '&prompt=' + encodedPrompt : '') : devinUrl ? devinUrl.includes('?') ? devinUrl + '&' + utm + agentParams : devinUrl + '?' + utm + agentParams : prompt ? 'https://app.devin.ai/?tags=' + tag + '&' + utm + agentParams + '&prompt=' + encodedPrompt : 'https://app.devin.ai/?' + utm + agentParams;
  const buttonLabel = type === 'schedule' ? 'Schedule in Devin ↗' : type === 'review' ? 'Set Up Devin Review ↗' : agent === 'advanced' ? 'Try in Devin ↗' : agent === 'dana' ? 'Try in Dana ↗' : agent === 'ada' ? 'Try in Ask Devin ↗' : 'Try in Devin ↗';
  const featureList = features ? features.split(',').map(f => f.trim()) : [];
  return <div className="uc-hero">
      <div className="uc-hero-inner">
        <div className="uc-hero-left">
          <h1 className="uc-hero-title">{title}</h1>
          <p className="uc-hero-desc">{description}</p>
          <div>
            <a href={devinHref} target="_blank" rel="noopener noreferrer" className="try-in-devin-btn">
              {buttonLabel}
            </a>
          </div>
        </div>
        <div className="uc-hero-meta">
          <div className="uc-meta-item">
            <span className="uc-meta-label">Author</span>
            <span className="uc-meta-value">Cognition</span>
          </div>
          <div className="uc-meta-item">
            <span className="uc-meta-label">Category</span>
            <span className="uc-meta-value">{category}</span>
          </div>
          {featureList.length > 0 && <div className="uc-meta-item">
              <span className="uc-meta-label">Features</span>
              <span className="uc-meta-value">{featureList.join(', ')}</span>
            </div>}
        </div>
      </div>
    </div>;
};

export const PromptBlock = ({children, type, agent, intent, playbookId}) => {
  var utm = 'utm_source=docs&utm_medium=use-case-gallery&utm_campaign=prompt-block';
  var tag = 'docs-use-case-gallery';
  var agentParams = (agent ? '&agent=' + agent : '') + (intent ? '&intent=' + intent : '') + (playbookId ? '&playbookId=' + playbookId : '');
  var label = type === 'schedule' ? 'Schedule in Devin' : type === 'playbook' ? 'Create Playbook' : type === 'knowledge' ? 'Add to Knowledge' : agent === 'advanced' ? 'Try in Devin' : agent === 'dana' ? 'Try in Dana' : agent === 'ada' ? 'Try in Ask Devin' : 'Try in Devin';
  var buildUrl = function (text) {
    var encoded = encodeURIComponent(text);
    if (type === 'schedule') return 'https://app.devin.ai/settings/schedules/create?' + utm + agentParams + '&prompt=' + encoded;
    if (type === 'playbook') return 'https://app.devin.ai/settings/playbooks/create?' + utm + '&body=' + encoded;
    if (type === 'knowledge') return 'https://app.devin.ai/knowledge?' + utm + '&body=' + encoded;
    if (agent === 'ada') return 'https://app.devin.ai/search?' + utm + '&noSubmit=true&prompt=' + encoded;
    return 'https://app.devin.ai/?tags=' + tag + '&' + utm + agentParams + '&prompt=' + encoded;
  };
  const ref = React.useRef(null);
  const [href, setHref] = React.useState('#');
  React.useEffect(() => {
    if (!ref.current) return;
    var codeEl = ref.current.querySelector('pre code');
    if (codeEl) {
      var text = codeEl.textContent.trim();
      if (text) setHref(buildUrl(text));
    }
    var header = ref.current.querySelector('[data-component-part="code-block-header"]');
    if (header && !header.querySelector('.prompt-block-devin-link')) {
      var link = document.createElement('a');
      link.href = href;
      link.target = '_blank';
      link.rel = 'noopener noreferrer';
      link.className = 'prompt-block-devin-link';
      link.style.cssText = 'display:inline-flex;align-items:center;gap:6px;text-decoration:none;color:#fff;font-size:11px;font-weight:500;padding:4px 10px;border-radius:6px;white-space:nowrap;background:#317CFF;transition:background 0.2s;margin-left:8px;';
      link.innerHTML = '<svg xmlns="http://www.w3.org/2000/svg" width="12" height="12" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"><path d="M18 13v6a2 2 0 0 1-2 2H5a2 2 0 0 1-2-2V8a2 2 0 0 1 2-2h6"/><polyline points="15 3 21 3 21 9"/><line x1="10" y1="14" x2="21" y2="3"/></svg> ' + label;
      link.onmouseenter = function () {
        link.style.background = '#2968D9';
      };
      link.onmouseleave = function () {
        link.style.background = '#317CFF';
      };
      header.appendChild(link);
    }
    var existingLink = ref.current.querySelector('.prompt-block-devin-link');
    if (existingLink && href !== '#') existingLink.href = href;
  });
  return <div className="prompt-block" ref={ref}>{children}</div>;
};

<UseCaseHero title="Evaluate 30 Logging Libraries for Your Stack" description="Run one Devin session per library to score pricing, performance, and SDK quality — then merge everything into a ranked comparison table." prompt="We're replacing our logging pipeline. Start a batch of 30 parallel Devin sessions — one per logging library — to research performance benchmarks, pricing tiers, language SDK quality, and retention policies. Compile all findings into a single comparison spreadsheet ranked by overall fit for a Node.js + Python microservices stack." category="Devin Optimization" features="Advanced" agent="advanced" intent="batch" />

<div className="uc-detail-wrapper">
  <Tip>Don't want to set this up manually? Paste a link to this page into a Devin session and ask it to set everything up for you.</Tip>

  <Steps>
    <Step title="Write a research prompt with a consistent template">
      The key to useful parallel research is giving every session the same checklist. Each session researches one library independently, so the template ensures results are directly comparable when merged.

      Open a new Devin session from the [Devin home page](https://app.devin.ai/?utm_source=docs\&utm_medium=use-case-gallery), or use the **Explore Advanced Capabilities** page on the Devin home page for a parallel research prompt template.

      <PromptBlock agent="advanced" intent="batch">
        ```txt Parallel logging library evaluation theme={null}
        We're replacing our ELK stack with a modern logging solution for a
        Node.js + Python microservices architecture (~50 services, ~2 TB logs/day).
        Research these logging libraries and platforms in parallel — one session
        per library:

        Datadog Logs, Grafana Loki, AWS CloudWatch Logs, Google Cloud Logging,
        Splunk, New Relic Logs, Axiom, Better Stack (Logtail), Mezmo (LogDNA),
        Logz.io, Papertrail, Sumo Logic, Elastic Cloud, Scalyr (Dataset),
        Timber.io, Seq, Graylog, Fluentd, Vector, Logstash, Syslog-ng,
        OpenTelemetry Collector, Cribl, Coralogix, Honeycomb, Baselime,
        Highlight.io, Signoz, Hyperdx, Last9

        For each library, fill in this template:
        - Type: SaaS platform, self-hosted, or agent/collector
        - Pricing model and estimated monthly cost for 2 TB/day ingestion
        - Log retention options (hot, warm, cold tiers)
        - Node.js SDK: quality 1-5, auto-instrumentation support (yes/no)
        - Python SDK: quality 1-5, auto-instrumentation support (yes/no)
        - Query language and avg query latency for 7-day window
        - Alerting: built-in rules, anomaly detection (yes/no)
        - Notable limitations or common complaints from developer forums

        Output as a markdown report with the template filled in.
        ```
      </PromptBlock>
    </Step>

    <Step title="Review and approve the proposed sessions">
      After submitting, Devin parses your list and proposes one session per library. You'll see a preview like:

      ```
      Proposed sessions (30):
        1. Research Datadog Logs — pricing, SDKs, retention, alerting...
        2. Research Grafana Loki — pricing, SDKs, retention, alerting...
        3. Research AWS CloudWatch Logs — pricing, SDKs, retention, alerting...
        ...
      ```

      Review the list and click **Approve** to launch all sessions simultaneously. Each session runs independently — browsing the library's website, reading documentation, checking developer forums, and filling in the template.

      If you want to skip or add libraries, edit the list before approving. You can also attach a [playbook](/product-guides/creating-playbooks) to ensure every session follows the same research methodology.
    </Step>

    <Step title="Collect and compare results">
      Once all sessions complete, Devin automatically merges the individual reports into a single comparison. The output follows whatever format you requested — here's what the compiled spreadsheet-style comparison looks like:

      ```
      ## Logging Library Comparison (Node.js + Python, 2 TB/day)

      | Library           | Type       | $/mo (2 TB/day) | Retention       | Node SDK | Python SDK | Query Lang   | Alerting     |
      |-------------------|------------|-----------------|-----------------|----------|------------|--------------|--------------|
      | Datadog Logs      | SaaS       | ~$5,400         | 15d hot, archive| 5/5      | 5/5        | Custom DSL   | Yes + anomaly|
      | Grafana Loki      | Self-host  | Infra only      | Configurable    | 4/5      | 4/5        | LogQL        | Via Grafana  |
      | Axiom              | SaaS       | ~$1,200         | 30d hot, 1yr    | 4/5      | 4/5        | APL          | Yes          |
      | Better Stack      | SaaS       | ~$890           | 30d default     | 5/5      | 4/5        | SQL-like     | Yes          |
      | Elastic Cloud     | SaaS/self  | ~$3,600         | ILM policies    | 5/5      | 5/5        | KQL / Lucene | Yes + ML     |
      | Signoz            | Self-host  | Infra only      | Configurable    | 4/5      | 4/5        | ClickHouse SQL| Yes         |
      | Coralogix         | SaaS       | ~$2,100         | Hot/warm/cold   | 4/5      | 3/5        | Lucene / SQL | Yes + anomaly|
      | ...               |            |                 |                 |          |            |              |              |

      ### Top 3 for a 50-service Node.js + Python stack:
      1. Axiom — lowest cost at scale, fast APL queries, solid SDKs
      2. Grafana Loki — zero license cost, pairs with existing Grafana dashboards
      3. Datadog Logs — best SDK auto-instrumentation, but expensive at 2 TB/day
      ```

      You can ask follow-up questions in the same session — it has context from all the child sessions.

      Once you've picked a winner, you can launch a Devin session directly from the same session to set up the library in your repo:

      <PromptBlock>
        ```txt Set up Axiom logging in our monorepo theme={null}
        Set up Axiom as our logging solution across our Node.js Express and
        Python FastAPI services. Install the SDKs, configure structured
        logging with correlation IDs, add the AXIOM_API_TOKEN from env vars,
        and verify logs are flowing by hitting a test endpoint. Open a PR
        with the setup.
        ```
      </PromptBlock>
    </Step>

    <Step title="Go deeper on the shortlist">
      Once you have a shortlist, start targeted follow-up sessions for deeper evaluation.

      <PromptBlock agent="advanced" intent="batch">
        ```txt Deep-dive top 3 logging solutions theme={null}
        Take Axiom, Grafana Loki, and Datadog Logs and do a deeper evaluation:
        - Build a proof-of-concept integration for each using our Node.js Express
          service and our Python FastAPI service
        - Ingest 10,000 sample log lines and measure ingestion latency
        - Run 5 realistic queries (error rate, P99 latency, trace correlation,
          free-text search, regex filter) and record response times
        - Document setup friction (account creation, SDK install, first log visible)
        Report which one was fastest to set up and queried most reliably.
        ```
      </PromptBlock>

      <PromptBlock agent="advanced" intent="batch">
        ```txt Apply the same pattern to APM tools theme={null}
        Use the same parallel research pattern to evaluate 15 APM / tracing
        platforms: Datadog APM, New Relic, Dynatrace, Honeycomb, Lightstep,
        Jaeger, Zipkin, Signoz, Grafana Tempo, AWS X-Ray, Google Cloud Trace,
        Elastic APM, Splunk APM, Highlight.io, Last9. Same template: pricing,
        SDK quality, query language, and notable limitations.
        ```
      </PromptBlock>
    </Step>

    <Step title="Tips">
      ### This pattern works for any technical evaluation

      Parallel research isn't limited to logging tools. Use it for any evaluation where you need the same data points about many options — CI/CD platforms, feature flag services, ORMs, cloud providers, or compliance frameworks. Example: "Research these 20 CI/CD platforms and compare build speed, pricing, self-hosted options, and GitHub integration quality."

      ### Keep each session scoped to 15-30 minutes

      If a single library needs hours of deep investigation, that's a sign it should be its own focused session rather than part of a parallel run. Parallel sessions work best when each item takes roughly the same amount of effort.
    </Step>
  </Steps>
</div>