Workspace
    • Briefing
    • Ask Airframe
    Transformation
    • Audit
    Your Stack
    • Registry
    • Finance
    • Context
    Discover
    Powered by Airframe
    1. Research
    2. /
    3. Products
    4. /
    5. NoBS
    NoBS

    NoBS

    AI Native

    Real tech, No BS.

    Est 2023|14 Ref Customers
    LinkedIn 906|Website|FTEs 43
    MarketsInfrastructure Monitoring
    NoBS screenshot
    FirmCompareTractionAnalysisAdvocates

    Insights

    All insightsAccountingFinanceSoftwareCustomer experience

    Benchmarks

    The Software LeaderboardMethodology

    Tools & data

    Market ExplorerStudioRegistry

    Company

    AboutCareers

    Legal

    Privacy PolicyTerms of Service

    © 2026 Airframe, Inc. All rights reserved.

      Published Oct 15, 2026

      01Common complaints

      - If you are not sure Datadog is the right long-term platform - NoBS’ specialization can accelerate Datadog adoption, which can raise switching costs if you later move to New Relic, Dynatrace, Grafana Cloud/LGTM, Elastic, etc. - If you require publicly documented security certifications - If your vendor risk program requires SOC 2 Type II and/or ISO 27001 evidence on a public trust page, NoBS does not appear to provide that publicly (based on available sources). - If you need broad transformation beyond observability - For large programs spanning cloud migration, app modernization, data platform work, and security governance, a broader SI may be more appropriate. - If your main problem is not “Datadog execution,” but “observability strategy” - Teams needing cross-vendor OpenTelemetry architecture, governance, and multi-backend portability may prefer vendor-agnostic specialists. - If budget constraints are tight and you can tolerate slower progress - Hiring/learning internally can be cheaper (cash-wise) but slower; NoBS is positioned as a premium acceleration layer. - Limited independent validation - NoBS has minimal third-party review presence on major platforms (G2 shows 0 reviews), reducing the ability to assess typical delivery quality and support experience. - Pricing transparency - No public pricing tiers were found; buyers should expect scoping calls and potentially variable pricing based on environment complexity. - Security/compliance documentation - No public SOC 2 / ISO documentation found; this can slow enterprise procurement. - Tool lock-in risk - NoBS is explicitly Datadog-only; teams looking for portability (e.g., OpenTelemetry-first with easy backend switching) should treat this as a strategic constraint.

      Deal disqualifiers: what makes a POOR fit

      • You want vendor-agnostic tool selection or are actively evaluating multiple platforms
      • You need a fully managed, round-the-clock NOC/MSP model with large-scale staffing guarantees
      • Your procurement requires published SOC 2/ISO certifications and they are non‑negotiable (NoBS does not publicly document these)

      02Why they buy

      - Datadog-only focus - NoBS repeatedly claims it is “the only consulting firm 100% focused on Datadog,” which—if true—would differentiate it from generalist consultancies. - Datadog recognition (Premier Partner status; DPN award claims) supports that it is meaningfully embedded in the Datadog ecosystem. - Delivery posture: engineer-led, low-fluff - NoBS explicitly differentiates from slide-heavy consulting and promotes directness (“Radical Best Intent”). - Outcomes aligned to common Datadog pain points - Cost leaks, tagging standards, and alert noise are recurring themes in Datadog community discussions; NoBS’ offerings map directly to these issues. - Balanced view: where competitors may have an advantage - Vendor-agnostic consultancies can provide more neutral tool selection. - Large SIs can provide scale, governance, and broader domain coverage.

      03Field reports

      Availability note (review platform coverage)

      - Gartner Peer Insights - Attempted to locate a Gartner Peer Insights profile/reviews specific to NoBS.tech. No accessible Gartner Peer Insights vendor page for NoBS was found via the automated research path; Gartner Peer Insights is primarily oriented around software products and may not list niche consulting firms. - G2 - G2 has a seller page for NoBS.tech with no publicly visible reviews at time of access. - TrustRadius - No meaningful TrustRadius product page for NoBS was found in accessible sources (TrustRadius appears more software-product focused).

      Vendor-published testimonial (positive)

      - NoBS homepage includes a customer quote attributed to a Tyler Technologies Senior Architect: - “Before working with NoBS, determining the root cause of CAD outages was a time-intensive process. Now, with Datadog's enhanced monitoring and tagging, issue diagnosis is significantly faster, reducing resolution time from prolonged delays to much shorter turnaround.” - Caveat - This is a vendor-selected testimonial; methodology and baselines (vendor-claimed magnitude of improvement) are not independently validated in the sources reviewed.

      Datadog-published partner case study (positive, but still marketing content)

      • Datadog’s case study on Nectar states that by working with NoBS to consolidate tools into Datadog, Nectar “eliminated redundant spending” and “expects to realize material monthly savings.”
      • Caveat
        • “Expects to realize” indicates projected savings rather than audited realized savings; also, Datadog case studies are marketing materials.

      Community sentiment (indirect but relevant)

      - Because NoBS is tightly coupled to Datadog outcomes, the largest pool of unfiltered feedback tends to be about Datadog itself. Common themes from Reddit/SRE/DevOps discussions that are relevant to what NoBS claims to help with: - Pricing confusion / cost creep - Example quote: “Honestly at this point I'm fairly certain Datadog's whole mission is just to rob everyone of their cloud budget.” (strongly worded, reflects frustration) - Example quote: “Datadog pricing is a mess…” (context: community-built calculator) - Operational sprawl / unused telemetry - Example quote: “We had custom metrics that literally nobody has queried in many months… health check logs just burning through our indexed volume…” - Interpretation (analyst view) - These complaints align with NoBS’ positioning around cost leaks, tagging strategy, and practical governance—however, they are not direct reviews of NoBS’ services.

      Nectar (Datadog partner case study)

      - Claimed outcome - Datadog case study: tool consolidation into Datadog with NoBS support reduced redundant spend; expected savings described as substantial monthly savings. - Critical evaluation - “Expected” savings are not the same as independently verified savings. - Case studies rarely describe total implementation cost, ongoing Datadog licensing impact, or what was de-scoped. - Still useful as directional evidence that NoBS is used for consolidation and cost rationalization.

      Tyler Technologies (NoBS site testimonial / case study link)

      - Claimed outcome - Vendor testimonial indicates incident/root-cause diagnosis improved dramatically, from a multi-week timeframe to a very short timeframe, with improved monitoring and tagging. - Critical evaluation - Strong claim with no published baseline methodology; could represent a specific incident class rather than typical outcomes. - The full case study was referenced on NoBS’ website but not fully accessible in the surfaced excerpt; buyers should request the full write-up and ask for measurable definitions (MTTR, MTTD, incident volume).

      Tribute Technology (PDF case study found)

      • Evidence
        • A Tribute Technology case study PDF references NoBS work (standardized tagging, etc.).
      • Critical evaluation
        • Third-party hosted PDFs can be marketing collateral; confirm authorship, date, and whether metrics are customer-verified.

      “Datadog Reality Check” (audit offering)

      • Evidence
        • NoBS positions this as an assessment to find weak spots, plus cost and coverage insights.
      • Critical evaluation
        • Audit-style engagements can deliver near-term improvements, but value depends heavily on:
          • Customer’s ability to execute remediation
          • Whether findings translate into lasting governance (tagging policy, service ownership, instrumentation standards)

      04Best fit

      Company sizes

      • Likely best fit
        • Mid-market to enterprise engineering organizations with meaningful production complexity and sufficient telemetry volume for governance to matter.
      • Also plausible
        • Well-funded startups scaling quickly on Datadog that need best practices early.

      Industries and verticals

      • Based on logos/testimonials shown on NoBS site, customers appear to span:
        • Public sector / gov-adjacent software (e.g., Tyler Technologies)
        • Higher education (Arizona State University logo shown)
        • Enterprise/industrial (ABB logo shown)
        • Financial services (1st Franklin Financial logo shown)
        • Others (varied logos shown)

      Roles and personas

      • Decision makers
        • VP Engineering, Head of Platform, Head of SRE/Infrastructure, Director of DevOps
      • End users
        • SREs, DevOps engineers, platform engineers, application owners who need usable dashboards/alerts/traces

      Pain points and challenges the product addresses

      • Datadog set up but not delivering outcomes (noise, poor tagging, unusable dashboards)
      • Migration from legacy monitoring tools with minimal “lift-and-shift” anti-patterns
      • Cost spikes and inability to forecast/budget observability spend
      • Lack of operational standards (service naming, ownership, SLO definitions)

      Qualification criteria: what makes a GREAT fit

      • You are committed to Datadog as the primary observability platform for the near-to-medium term
      • You can grant access and allocate internal engineers to implement recommended changes
      • You value direct, opinionated feedback and are willing to change instrumentation/tagging standards

      05The pitch

      What the product does (core value proposition in objective terms)

      - NoBS is a services firm (not a SaaS product) that provides hands-on Datadog implementation, optimization, migration, and ongoing support—positioned as “real engineers” rather than ticket-based support tiers. It emphasizes practical outcomes such as better tagging, dashboards, monitors, SLOs, alerting hygiene, and cost/capability audits. - Core service lines highlighted by NoBS include: - Datadog implementations (setup, tagging strategy, dashboards, integrations) - Configuration & best practices (monitors, SLOs, alerting, tagging) - Ongoing support (“no tickets, no tiers”) - “Datadog Reality Checks” (audit-style assessments including cost & coverage insights) - Bespoke monitoring solutions for edge cases / legacy stacks - Migrations to Datadog (from “legacy tools”)

      Target market and market positioning

      • Target buyers appear to be engineering-led organizations already committed to Datadog (or moving to it) that want faster time-to-value, reduced alert noise, and better governance/cost control.
      • Market positioning is intentionally “anti-consulting-theater”: minimal slide decks, opinionated best practices, direct feedback (“Radical Best Intent”), and engineering-led delivery.

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

      Download full report →
      • If you are not sure Datadog is the right long-term platform

        • NoBS’ specialization can accelerate Datadog adoption, which can raise switching costs if you later move to New Relic, Dynatrace, Grafana Cloud/LGTM, Elastic, etc.
      • If you require publicly documented security certifications

        • If your vendor risk program requires SOC 2 Type II and/or ISO 27001 evidence on a public trust page, NoBS does not appear to provide that publicly (based on available sources).
      • If you need broad transformation beyond observability

        • For large programs spanning cloud migration, app modernization, data platform work, and security governance, a broader SI may be more appropriate.
      • If your main problem is not “Datadog execution,” but “observability strategy”

        • Teams needing cross-vendor OpenTelemetry architecture, governance, and multi-backend portability may prefer vendor-agnostic specialists.
      • If budget constraints are tight and you can tolerate slower progress

        • Hiring/learning internally can be cheaper (cash-wise) but slower; NoBS is positioned as a premium acceleration layer.
      • Limited independent validation

        • NoBS has minimal third-party review presence on major platforms (G2 shows 0 reviews), reducing the ability to assess typical delivery quality and support experience.
      • Pricing transparency

        • No public pricing tiers were found; buyers should expect scoping calls and potentially variable pricing based on environment complexity.
      • Security/compliance documentation

        • No public SOC 2 / ISO documentation found; this can slow enterprise procurement.
      • Tool lock-in risk

        • NoBS is explicitly Datadog-only; teams looking for portability (e.g., OpenTelemetry-first with easy backend switching) should treat this as a strategic constraint.
      • Datadog-only focus
        • NoBS repeatedly claims it is “the only consulting firm 100% focused on Datadog,” which—if true—would differentiate it from generalist consultancies.
        • Datadog recognition (Premier Partner status; DPN award claims) supports that it is meaningfully embedded in the Datadog ecosystem.
      • Delivery posture: engineer-led, low-fluff
        • NoBS explicitly differentiates from slide-heavy consulting and promotes directness (“Radical Best Intent”).
      • Outcomes aligned to common Datadog pain points
        • Cost leaks, tagging standards, and alert noise are recurring themes in Datadog community discussions; NoBS’ offerings map directly to these issues.
      • Balanced view: where competitors may have an advantage
        • Vendor-agnostic consultancies can provide more neutral tool selection.
        • Large SIs can provide scale, governance, and broader domain coverage.
      • Gartner Peer Insights
        • Attempted to locate a Gartner Peer Insights profile/reviews specific to NoBS.tech. No accessible Gartner Peer Insights vendor page for NoBS was found via the automated research path; Gartner Peer Insights is primarily oriented around software products and may not list niche consulting firms.
      • G2
        • G2 has a seller page for NoBS.tech with no publicly visible reviews at time of access.
      • TrustRadius
        • No meaningful TrustRadius product page for NoBS was found in accessible sources (TrustRadius appears more software-product focused).
      • NoBS homepage includes a customer quote attributed to a Tyler Technologies Senior Architect:
        • “Before working with NoBS, determining the root cause of CAD outages was a time-intensive process. Now, with Datadog's enhanced monitoring and tagging, issue diagnosis is significantly faster, reducing resolution time from prolonged delays to much shorter turnaround.”
      • Caveat
        • This is a vendor-selected testimonial; methodology and baselines (vendor-claimed magnitude of improvement) are not independently validated in the sources reviewed.
      • Because NoBS is tightly coupled to Datadog outcomes, the largest pool of unfiltered feedback tends to be about Datadog itself. Common themes from Reddit/SRE/DevOps discussions that are relevant to what NoBS claims to help with:
        • Pricing confusion / cost creep
          • Example quote: “Honestly at this point I'm fairly certain Datadog's whole mission is just to rob everyone of their cloud budget.” (strongly worded, reflects frustration)
          • Example quote: “Datadog pricing is a mess…” (context: community-built calculator)
        • Operational sprawl / unused telemetry
          • Example quote: “We had custom metrics that literally nobody has queried in many months… health check logs just burning through our indexed volume…”
      • Interpretation (analyst view)
        • These complaints align with NoBS’ positioning around cost leaks, tagging strategy, and practical governance—however, they are not direct reviews of NoBS’ services.
      • Claimed outcome
        • Datadog case study: tool consolidation into Datadog with NoBS support reduced redundant spend; expected savings described as substantial monthly savings.
      • Critical evaluation
        • “Expected” savings are not the same as independently verified savings.
        • Case studies rarely describe total implementation cost, ongoing Datadog licensing impact, or what was de-scoped.
        • Still useful as directional evidence that NoBS is used for consolidation and cost rationalization.
      • Claimed outcome
        • Vendor testimonial indicates incident/root-cause diagnosis improved dramatically, from a multi-week timeframe to a very short timeframe, with improved monitoring and tagging.
      • Critical evaluation
        • Strong claim with no published baseline methodology; could represent a specific incident class rather than typical outcomes.
        • The full case study was referenced on NoBS’ website but not fully accessible in the surfaced excerpt; buyers should request the full write-up and ask for measurable definitions (MTTR, MTTD, incident volume).
      • NoBS is a services firm (not a SaaS product) that provides hands-on Datadog implementation, optimization, migration, and ongoing support—positioned as “real engineers” rather than ticket-based support tiers. It emphasizes practical outcomes such as better tagging, dashboards, monitors, SLOs, alerting hygiene, and cost/capability audits.
      • Core service lines highlighted by NoBS include:
        • Datadog implementations (setup, tagging strategy, dashboards, integrations)
        • Configuration & best practices (monitors, SLOs, alerting, tagging)
        • Ongoing support (“no tickets, no tiers”)
        • “Datadog Reality Checks” (audit-style assessments including cost & coverage insights)
        • Bespoke monitoring solutions for edge cases / legacy stacks
        • Migrations to Datadog (from “legacy tools”)