--- title: "Low DevOps performers fail 40% of changes; elite teams fail 5%" summary: "What DORA's 2024 and 2025 reports measured on delivery, AI and platforms, and how 28 DevOps toolchain products bill, with Indian prices and rules, as of September 2026." url: https://www.thetechbag.com/blog/benefits-challenges-implementing-devops-large-enterprises format: Analysis desk: "Cloud & DevOps" published: 2025-06-11 facts_checked: 2026-09-30 author: TechBag (The TechBag Journal) tags: ["DevOps","DORA","change failure rate","AI assistants","platform engineering","CI/CD","GitHub","GitLab","pricing","CERT-In","GST"] cover: https://www.thetechbag.com/blog/covers/benefits-challenges-implementing-devops-large-enterprises.png --- # Low DevOps performers fail 40% of changes; elite teams fail 5% *What DORA's 2024 and 2025 reports measured on delivery, AI and platforms, and how 28 DevOps toolchain products bill, with Indian prices and rules, as of September 2026.* Analysis · Cloud & DevOps · By TechBag · Published 2025-06-11 · Facts checked 2026-09-30 · Canonical: https://www.thetechbag.com/blog/benefits-challenges-implementing-devops-large-enterprises The short version - The benefit is real and measurable: in DORA’s 2024 clusters, elite teams deploy on demand, take under a day from commit to production and fail 5% of changes; low performers deploy between monthly and twice a year and fail 40%.[1] - The challenges a large enterprise meets in 2026 are AI and platforms, not culture slides. DORA found AI adoption tied to lower delivery stability in 2024 and again in 2025, when 90% of respondents used AI and 90% of organisations had adopted at least one platform.[2] [3] - The third challenge is the bill. Of 28 developer-tool products in TechBag’s guide, 14 price per seat, 7 by consumption and 7 only by quote; three meter CI minutes on top of the seat.[4] The 2023 version of this post listed four benefits, four challenges and four best practices, and supported them with five statistics: 46 times more deployments, a 200-fold faster turnaround, a 60% drop in failed releases, a 63% better chance of meeting goals, and a Gartner forecast for 2022. None carried a date or a link we could follow, so they are gone. The question a large Indian enterprise asks has not changed: is DevOps worth the disruption at our size, and what goes wrong when a company with legacy systems, a separate operations team and an audit function tries it? DORA, the research programme now run inside Google Cloud, has measured exactly this in an annual survey for years, and its numbers are more useful than any of the five. ## The benefit, measured: four numbers separate elite from low DORA measures software delivery with four keys: how often a team deploys, how long a change takes from commit to production, what share of changes fail, and how fast the team recovers from a failed deployment. In its 2024 report, elite teams deploy on demand, take less than a day per change, fail 5% of changes and recover in under an hour. Low performers deploy between once a month and once every six months, take one to six months per change, fail 40% and take a week to a month to recover. Elite teams are under a fifth of organisations.[1] **Figure: Low performers' changes fail eight times as often as elite teams'; the middle is out of order** *Change failure rate by DORA 2024 performance cluster, % of changes to production* Elite deploys on demand 5% High daily to weekly 20% Medium weekly to monthly 10% Low monthly to twice a year 40% | | Value (%) | | --- | --- | | Elite | 5 | | High | 20 | | Medium | 10 | | Low | 40 | Source: DORA, Accelerate State of DevOps 2024, cluster table as summarised by Octopus Deploy · as of 30 September 2026 · Clusters come from survey cluster analysis; thresholds move from year to year ReportedThe inversion In 2024 the high cluster failed 20% of changes and the medium cluster 10%. DORA’s clusters are not a ladder where every metric improves together: the high group trades stability for speed. For a large enterprise that is the useful warning, because speed is what a DevOps programme is usually sold on.[1] The benefit the original promised, “faster time to market” with “quality improvement”, is therefore true only for the teams that get both. The four keys are cheap to measure from the systems a large enterprise already runs: the deployment log, the change calendar and the incident tool. Measure them before the programme starts, or you will never know which cluster you moved from. Large enterprises usually find their lead time is set not by engineering but by approval. A change advisory board that meets weekly puts a floor of days under every change, however fast the pipeline is. The answer is not to abolish the board, which an auditor will ask about, but to move routine, tested, reversible changes to a standard-change path with automated evidence, and keep the board for the changes that genuinely need judgement. That is the original’s “organisational culture” challenge in a form a risk committee can sign. ## AI made developers feel faster and delivery less stable In the 2024 report, more than 75% of respondents relied on AI for at least one daily task. DORA estimated that a 25% increase in AI adoption went with a 7.5% rise in documentation quality, 3.4% in code quality and 3.1% in code review speed, and with a 1.5% fall in delivery throughput and a 7.2% fall in delivery stability. 39% reported little or no trust in AI-generated code.[2] **Figure: In DORA's 2024 data, AI improved the code and cost the delivery** *Estimated change associated with a 25% increase in AI adoption, DORA 2024 survey* What went up - Documentation quality, +7.5% - Code quality, +3.4% - Code review speed, +3.1% What went down - Delivery stability, −7.2% - Delivery throughput, −1.5% Source: Google Cloud, Announcing the 2024 DORA report · as of 30 September 2026 · Associations from survey data, not causal The 2025 report, published on 24 September 2025 from nearly 5,000 respondents, moved one of those lines. AI use reached 90%, more than 80% said it had raised their productivity, and the share with little or no trust in AI code fell to 30%. AI adoption now showed a positive relationship with throughput, but the relationship with delivery stability was still negative.[3] DORA’s 2025 report frames AI as an amplifier of whatever a team already is: fast feedback and small batches get faster, weak testing and large batches break more often. Our view Our view: in a large enterprise, gate AI-assistant rollout on the change failure rate, not on seat requests. A team whose failure rate is rising does not get more AI until its tests catch what the assistant writes. ## Platforms: 90% have one, and the first year can cost performance The original’s answer to scale was “start small” and “build a strong team”. DORA’s answer is the internal developer platform: a paved road of templates, pipelines and environments that product teams use on their own. In 2024 DORA found platforms raise developer productivity, are more common in larger organisations, and can bring a temporary dip in performance before the gains arrive; results depend on treating the platform as a product with its developers as users.[2] By 2025, 90% of organisations had adopted at least one platform.[3] **Figure: Start with one value stream, a measured baseline and a platform run as a product** *A rollout sequence for a large enterprise, built from DORA's 2024 and 2025 findings* 1. 01Baseline one value streamPick one product line with a real release cadence. Record the four keys from the deployment log and incident tool. 2. 02Build the paved roadOne pipeline template, one secrets store, one way to get an environment. A team owns it and treats developers as its users. 3. 03Gate AI on stabilityRoll out the assistant where tests and review already catch defects; hold it where the change failure rate is rising. 4. 04Re-measure, then widenExpect a dip in the first quarters. Add the next value stream only when the four keys have recovered. Source: Google Cloud, 2024 and 2025 DORA report announcements; TechBag synthesis · as of 30 September 2026 Legacy systems, the original’s second challenge, belong in step one. A mainframe or a vendor-hosted core system with a monthly release window is a fixed constraint on the value stream. Measure it honestly and decouple around it, rather than counting it as a failure of the programme. ## The toolchain bill: three meters, and a quarter of products quote only A DevOps programme buys a toolchain, and a large enterprise discovers the meters only at renewal. TechBag’s developer tools guide, last reviewed on 24 August 2026, lists 28 products by SKU across nine vendors: GitHub, GitLab, Atlassian, Postman, HashiCorp, JFrog, Sonar, Sonatype and Kong.[4] TechBag countTechBag count, developer tools guide Of 28 SKUs, 14 are licensed per seat, 7 by consumption and 7 only by quote. Three meter CI minutes separately from the seat (GitHub Enterprise, the GitLab DevSecOps Platform and Bitbucket). Four sell the AI assistant as an add-on. Seventeen can be self-hosted, and seven document an Indian region: JFrog’s four products, Sonatype Nexus Repository, Kong Konnect and Kong AI Gateway.[4] **Figure: Half of the DevOps toolchain prices per seat; a quarter will not quote until you call** *Developer-tool SKUs by licence model, count, TechBag guide reviewed 24 August 2026* - Per seat14 SKUs 50% - Consumption (resources, storage, calls)7 SKUs 25% - Quote only7 SKUs 25% | | Value (SKUs) | Share | | --- | --- | --- | | Per seat | 14 | 50% | | Consumption (resources, storage, calls) | 7 | 25% | | Quote only | 7 | 25% | Source: TechBag developer tools guide, 28 SKUs across 9 vendors; TechBag count · as of 30 September 2026 The meters matter because they move with the success of the programme. More deployments mean more CI minutes; more infrastructure as code means more managed resources on a per-resource meter; a wider AI rollout means more add-on seats. Budget the second year at the deployment rate you are aiming for, not the one you have. The usual escape from the minutes meter is self-hosted runners: build machines you already own, registered with GitHub or GitLab, so the pipeline stops consuming metered minutes. The guide is blunt about the trade: they are infrastructure you now maintain and secure, and a compromised runner is a supply-chain problem, because it holds the credentials every deployment uses.[4] For a large enterprise with a data centre and a security team that is often the right trade. For a business unit without either, the meter is cheaper than the incident. If you are buying this in India **Price.** The guide records these products in US dollars; buy at US list through a reseller in INR, plus 18% GST, or pay the foreign invoice with 18% IGST under reverse charge as an OIDAR service.[5] One worked line: Postman’s Team plan at US$19 a user a month, billed annually, for 50 developers is US$11,400 a year, about ₹9,46,200 at ₹83 to the dollar and ₹11,16,516 with GST.[4] **Regulation.** CERT-In’s Directions of 28 April 2022 require incidents to be reported within six hours and logs kept for 180 days within India; pipeline and deployment logs are part of that estate.[6] SEBI’s Cybersecurity and Cyber Resilience Framework has applied to regulated entities since 31 August 2025, and RBI’s Directions of 31 July 2026 ask banks for vendor contracts with audit and RBI inspection rights, which covers the SaaS half of a toolchain.[7] [8] The DPDP Rules, notified on 13 November 2025, bring security-safeguard and breach-intimation duties into force on 13 May 2027; test data copied from production into a pipeline is personal data under them.[9] For most products in the guide, self-hosting is the documented route to keeping repositories in India. How we did this Figures as of 30 September 2026 The cluster values are DORA’s 2024 Accelerate State of DevOps report as tabulated by Octopus Deploy; DORA’s own report page was read but its PDF was not, and cluster shares are given only as “under a fifth” because published summaries disagree on the exact split. AI and platform findings are from Google Cloud’s announcements of the 2024 and 2025 reports. The licence-model count is TechBag’s, from the developer tools guide as it stood on 30 September 2026 (28 SKUs, reviewed 24 August 2026); each SKU is counted once by its primary meter. INR uses ₹83 to the dollar and adds 18% GST. The five statistics in the 2023 original were removed because no dated source could be found for them. Spotted an error? Write to us; corrections are published at the foot of the piece. Sources 1. [Octopus Deploy (Steve Fenton), The 2024 DevOps performance clusters, summarising DORA's Accelerate State of DevOps 2024](https://octopus.com/blog/2024-devops-performance-clusters) — 19 November 2024 2. [Google Cloud, Announcing the 2024 DORA report (AI adoption effects; platform engineering)](https://cloud.google.com/blog/products/devops-sre/announcing-the-2024-dora-report) — 23 October 2024 3. [Google Cloud, Announcing the 2025 DORA report: State of AI-assisted Software Development](https://cloud.google.com/blog/products/ai-machine-learning/announcing-the-2025-dora-report) — 24 September 2025 4. [TechBag, Developer tools guide (28 SKUs, licence models, CI minutes, AI licensing, self-hosting, India region, Postman Team price)](https://www.thetechbag.com/browse/devops/developer-tools) — reviewed 24 August 2026 5. [India Briefing, OIDAR services: GST and reverse charge](https://india-briefing.com/news/tax-digital-services-oidar-in-india-gst-applicability-and-compliance-22465.html) — 29 September 2023 6. [CERT-In, Directions under section 70B(6) of the IT Act, 2000 (six-hour reporting; 180-day logs within India)](https://www.cert-in.org.in/PDF/CERT-In_Directions_70B_28.04.2022.pdf) — 28 April 2022 7. [SEBI, Cybersecurity and Cyber Resilience Framework (CSCRF) for SEBI Regulated Entities](https://www.sebi.gov.in/legal/circulars/aug-2024/cybersecurity-and-cyber-resilience-framework-cscrf-for-sebi-regulated-entities-res-_85964.html) — 20 August 2024; in force 31 August 2025 8. [RBI, Cybersecurity, Technology Risk and Resilience Framework Directions, 2026, via practitioner summary](https://taxguru.in/rbi/rbi-issues-commercial-banks-cybersecurity-technology-risk-resilience-framework-directions-2026.html) — 31 July 2026 RBI PDF not fetched. 9. [Legismith Partners, DPDP Rules 2025 commencement timeline](https://legismith.com/dpdp-rules-2025-timeline/) — Rules notified 13 November 2025 Related on TechBag: the [developer tools guide](https://www.thetechbag.com/browse/devops/developer-tools) carries the 28 SKUs counted here; the [GitLab DevSecOps Platform page](https://www.thetechbag.com/gitlab/gitlab-devsecops-platform) covers the single-platform option and its self-managed route; the [observability guide](https://www.thetechbag.com/browse/devops/observability-apm) covers the tools that measure recovery time. **Disclosure.** TechBag is a software reseller: it earns a margin when a reader buys through it, including from vendors named here. The analysis is TechBag’s own; no vendor paid for or saw this piece before publication. Facts are labelled reported, TechBag count or our view. Go deeper on TechBag - [Developer tools guide](https://www.thetechbag.com/browse/devops/developer-tools) — the 28 SKUs and three licence meters counted here - [GitLab DevSecOps Platform](https://www.thetechbag.com/gitlab/gitlab-devsecops-platform) — the single-platform option and its self-managed route to India residency - [Observability & APM guide](https://www.thetechbag.com/browse/devops/observability-apm) — the tools that measure recovery time