Last9

Name: Last9
Brand: Last9
Rating: 4.7 (51 reviews)

AI Native

Observability for AI Native Teams!

Est 2020|Valuation $53.1M|Raised $15.1M|12 Ref Customers

LinkedIn 10K|Website|Web traffic 36K|FTEs 40|HQ Sunnyvale, California, US

MarketsInfrastructure Monitoring Observability Platform Application Performance Monitoring (APM)

Published Oct 15, 2026

01Common complaints

- If you want the broadest, most mature “one-stop” observability suite - Datadog is repeatedly perceived as broader in features/integrations; if you rely heavily on niche integrations, Last9 may feel incomplete. - If your telemetry volume is highly volatile and you cannot enforce governance - Event-based pricing plus “ingest everything” behavior can still lead to unpredictable cost. If you can’t control event volume, you may struggle to forecast. - If you require publicly documented, extensive compliance posture - SOC 2 Type II is publicly documented, but ISO/HIPAA/PCI and detailed security feature documentation were not found in this research. - If you need long retention for logs/traces on standard plans - The Pro tier lists 14-day retention for logs and traces; if you need 30–90+ days routinely, you may need Enterprise pricing. - If you need deep adjacent capabilities (beyond observability) - For example, if your buying center wants security monitoring/SIEM, RUM, synthetics, CI visibility, etc., you may prefer vendors that bundle those capabilities. - Feature/integration breadth vs incumbents - Users in G2 comparisons report less breadth vs Datadog. - Learning curve for advanced features - G2’s aggregated summary indicates new users may face a learning curve with advanced functionality. - Limited publicly accessible negative-review detail in this research - While G2 has 50+ reviews, this research snapshot did not extract representative 1–2 star quotes due to page depth/navigation constraints. - Security/compliance documentation gaps - SOC 2 Type II is public, but ISO 27001/other certifications and detailed control lists were not found in accessible sources.

02Why they buy

- Potential unique selling points (supported by available evidence) - High-cardinality workflows and “slice by any label” positioning. - Unified correlation across logs, metrics, traces. - A telemetry control plane that claims to apply cost controls before storage. - A developer/AI-agent workflow via an MCP server (open-source presence on GitHub and third-party MCP directories). - Where competitors clearly have advantages - Datadog: breadth of features and integrations. - Established vendors: longer track record, potentially more enterprise references, and mature compliance documentation.

03Field reports

> Note: Some platforms may be vendor-incentivized or “invited by seller.” Treat review sources as directional, and triangulate with independent community discussions. - Review platform availability - G2: Last9 has a substantial review presence (51 reviews shown on the product page). - TrustRadius: Direct Last9 product reviews were not found in the searches performed; TrustRadius pages accessed were about TrustRadius generally rather than Last9. - Gartner Peer Insights: A Last9 listing/reviews page was not found in accessible results; Gartner Peer Insights can be hard to access and discover without exact product taxonomy. - Positive review themes (G2) - Debugging across many microservices and finding relevant logs/services quickly is a commonly praised capability. - Example positive quote (G2 review): - “Recently, I had to investigate an incident across nearly 20 microservices. With Last9, it was easy to search for the exact service I needed and then check the logs to trace the issue. That saved me a lot of time…” (Reviewer: Software Engineer, Aug 25, 2025). - G2’s AI-generated summary (based on reviews) highlights “reliable observability,” “intuitive dashboards,” actionable metrics, and proactive alerting; it also mentions a learning curve for advanced features. - Negative review themes (what’s visible) - Within the accessible G2 snippet, explicit 1–2 star quotes were not captured in the tool output. This is a research limitation: the review list is large and typically requires deeper page navigation to extract representative negative quotes. - However, G2’s Datadog vs Last9 comparison page includes a summarized tradeoff: users report Last9 “lacks the same breadth of features and integrations as Datadog.” This aligns with a common buyer concern when choosing newer observability vendors. - Community / social (Reddit) sentiment - A Reddit AMA by Last9’s CEO exists, which is useful for understanding positioning and leadership perspectives, but it’s not the same as independent customer feedback. - Additional Reddit discussions surfaced are more about observability concepts (e.g., high-cardinality internals, Prometheus vs ClickHouse) and sometimes link to Last9 blog posts; these indicate brand presence in practitioner communities but don’t substitute for “user review” evidence. - Why customers chose Last9 (evidence available) - Vendor and marketplace positioning emphasize: - High-cardinality support - Correlation across logs/traces/metrics - Cost controls before storage - Faster triage/root cause analysis - G2 review quote supports “faster incident investigation” as a concrete selection reason. - Why some customers might leave / not choose (evidence available) - Comparative review summary suggests feature/integration breadth may lag mature incumbents (Datadog). - If your org is deeply invested in a broad ecosystem of prebuilt integrations or niche monitoring products, switching costs and missing functionality can be a deal-breaker. - Probo case study (vendor PDF) - Claim: “Probo cuts monitoring costs by 90% with Last9” (vendor-published PDF). - Critical evaluation - The “90%” savings is a strong claim, but it is vendor-published; methodology, baseline spend, and what was included/excluded (e.g., data egress, retention changes, reduced coverage) are not independently validated. - Cost reductions in observability frequently come from changes like filtering logs, reducing retention, re-aggregating metrics, or changing sampling—buyers should ask whether reliability/coverage was impacted. - Video streaming scale case study (vendor PDF) - A Last9 customer PDF references observability for “50+ million concurrent live streaming viewers” (vendor-published). - Critical evaluation - These scale claims are compelling but hard to verify without: - Named customer disclosure (if not explicit) - Architecture diagrams and workload detail - Independent benchmarks - Contractual scope (what components were covered)

04Best fit

- Company sizes - Likely best fit: mid-market to enterprise engineering orgs running microservices and multi-tenant systems (often 50–2,000+ employees). One G2 reviewer profile shown was “Mid-Market (51–1000 emp.).” - Industries and verticals - Streaming/media and high-scale consumer platforms are suggested by vendor/press references (e.g., Disney+ Hotstar in press; streaming concurrency case study). - SaaS/multi-tenant products that need tenant-level visibility. - Roles and personas - Decision makers: Head of Platform/SRE/Infrastructure, VP Engineering, CTO; sometimes FinOps. - End users: SREs, platform engineers, backend engineers, on-call responders. - Pain points and challenges the product addresses - High-cardinality metrics pain (exploding label space, expensive active series constraints, slow queries). - Slow incident triage when logs/metrics/traces are in separate tools. - Rising observability spend and lack of cost controls. - Qualification criteria: what makes a GREAT fit - You already use (or can adopt) OpenTelemetry and/or Prometheus pipelines. - You have real cardinality issues (tenant/user/route-level debugging needs). - You can operationalize ingestion governance (drop noise, route selectively) and have predictable telemetry engineering practices. - Deal disqualifiers: what makes a POOR fit - You require a massive ecosystem of out-of-the-box integrations and “everything suite” features today. - You need compliance certifications beyond SOC 2 Type II that are not publicly documented (e.g., ISO 27001, HIPAA) and cannot accept vendor-provided evidence.

05The pitch

- What the product does (core value proposition in objective terms) - Last9 positions itself as a unified observability platform focused on high-cardinality telemetry across metrics, logs, traces (and profiles), with an emphasis on faster incident triage and “full-fidelity” correlation across signals. It also markets a “control plane” to route/transform telemetry and apply cost controls before storage, plus AI-assisted workflows (“Agentic DX”) including an MCP server for AI-agent access to production telemetry. - The product messaging strongly centers on eliminating “rip-and-replace,” supporting open standards (OpenTelemetry + Prometheus compatibility), and avoiding per-host/per-user pricing typical of incumbents. - Target market and market positioning - Target users: SRE, platform engineering, DevOps, and application developers who need to debug distributed systems (microservices) and who experience pain from high-cardinality metrics and/or high-volume telemetry. - Market positioning: “high-cardinality observability at scale” and “triage faster” positioned against Datadog/New Relic/Grafana Cloud, with differentiation around cost controls, rich dimensionality (tenant/user/route labels), and correlation. - Company background (founding year, HQ, key leadership) - Founded: 2020 (reported in press coverage). - HQ: Reported as California-headquartered in VentureBeat coverage. - CEO/cofounder: Nishant Modak (named in VentureBeat and a public Reddit AMA post). - Funding and growth: investment rounds, acquisitions, estimated customer count/revenue if public - Funding (publicly reported): VentureBeat reported Last9 emerging from stealth with an $11M Series A led by Sequoia Capital India (now Peak XV Partners) in April 2022. - Customer examples mentioned in press/market listings include Disney+ Hotstar and others (not independently verified as current customers). - Revenue/customer count: Not publicly disclosed in the sources accessed. - Acquisitions: No acquisitions found in the sources reviewed. - Pricing model with specific tiers and costs where available - Vendor-published “Transparent pricing” highlights a Pro tier at **$1,150/month** including **1B events/month** and usage pricing beyond that, with “unlimited team members,” “unlimited ingestion rules,” and retention of **90 days for metrics** and **14 days for logs and traces** (as listed on the website). - Enterprise tier is quoted as custom/commitment pricing with options like “Bring your own cloud,” custom retention, and 24×7×365 support. - Pricing positioning emphasizes no per-host/node/user charges. - Total cost of ownership (TCO) considerations (implementation, training, hidden costs) - Potential TCO positives - If your costs currently explode due to per-host pricing (and/or high-cardinality limits/penalties), event-based pricing plus ingestion controls may reduce spend—assuming your event volume is predictable and governance is strong. - “Agentless / no rip-and-replace” claims suggest shorter rollout for teams already using OTel/Prometheus. - Potential TCO risks - Event-based pricing can become unpredictable if telemetry volume grows rapidly (new endpoints, verbose logs, bursty traces, or accidental label explosions). Buyer diligence should include forecasting and guardrails. - Advanced feature learning curve is mentioned in G2’s aggregated review summary (and is typical for observability tooling). - Migration costs (dashboards, alerts, historical data retention) may still be substantial despite “one-click” claims. - Key competitors in the space (list 4-6 direct alternatives) - Datadog - New Relic - Grafana Cloud - Honeycomb - Observe, Inc. - Better Stack

Get a comprehensive analysis of Last9 including market position, competitive landscape, adoption trends, and peer benchmarks.

Download full report →