Prevent outages before customers feel them
Catch regressions in PRs and pre-production, before customers see failures.
- Jide nlọghachi azụ tupu mwepụta
- Belata ọnụego ọdịda mgbanwe
- Nyefee ngwa ngwa na ntụkwasị obi
Zof ghọtara sistemụ nyocha gị na-echebe.
Ikpo okwu na-aga n'ihu na-esetịpụ ọrụ, ndabere, yana pipeline CI/CD na-ebuba koodu n'ime ha. Ihe mgbaàmà ihe ize ndụ na-agbasa n'akụkụ eserese ahụ ka nlọghachi azụ n'otu ọrụ na-ebuli ihe ọ bụla ọ metụrụ aka.
MAPỤTA ELU
Ọrụ 20
Gafee kwụ n'ahịrị, cache, ndị nnọchite na mpụga.
GBANWEE mmata
Ọnọdụ CI/CD
Pipeline dị n'akụkụ eserese.
Mgbasa ihe ize ndụ
Mgbama n'ọkwa ihu
Ọdịda na-eme njem na ndabere.
- 01 · SERVICE TOPOLOGY
20 services
28 dependency edges
- 02 · RISK SIGNALS
2 active
83% coverage observed
- 03 · CI/CD AWARENESS
Build succeeded
- Azure DevOps
- 8m 22s
Ọnụ ahịa ọdịda n'ezie
Ihe omume mmepụta na-emetụta ego, ntụkwasị obi onye ahịa, na ọsọ injinịa. A pụrụ igbochi ọtụtụ na ha site na atụmatụ nkwenye ziri ezi.
$5.6M
Ọnụ ahịa nkezi kwa awa nke oge dara ada (enterprise)
Mfu ego
Mmetụta ego kpọmkwem site na enweghị ọrụ na ọdịda azụmahịa
80%
Nke ọdịda mgbanwe kpatara, ọ bụghị akụrụngwa
Ntụkwasị obi onye ahịa na ọpụpụ
Mmebi aha ụlọ ọrụ ogologo oge na ọpụpụ onye ahịa site na nsogbu ntụkwasị obi
60%
Nke ihe omume a pụrụ igbochi site na nnwale tupu mmepụta ka mma
Nbibi injinịa
Ike ọgwụgwụ otu, mgbanwe ọnọdụ, na ọrụ atụmatụ gbara afọ site na nzaghachi ihe omume
Ihe kpatara mgbochi ji dị mkpa karịa nzaghachi: Ọ bụ ezie na nzaghachi ihe mberede dị mkpa, igbochi ọdịda tupu ha eru na mmepụta na-ebelata ọnụ ahịa, na-echekwa ntụkwasị obi ndị ahịa, ma na-eme ka ndị otu injinia lekwasị anya n'iwu ihe kama ịgbanyụ ọkụ.
Ihe kpatara mkpọchi ji ka na-eme (ọbụna na nlekota)
Ụzọ ọdịnala na-ejide nsogbu mgbe ha mechara. Mgbochi chọrọ nkwado tupu mmepụta.
Nlekota na-achọpụta ọdịda mgbe mmetụta gasịrị
Ngwaọrụ nlekota na-adọ gị aka ná ntị mgbe ihe mebiri, mana ka ọ na-eru, ndị ahịa enwetalarị mmetụta.
Edemede na-emebi ka sistemu na-agbanwe
Ụyọkọ nnwale na-aghọ ihe na-agbawa agbawa ka ngwa ọrụ na-agbanwe, na-ekepụta oghere na mkpuchi.
Mkpuchi nnwale ahaghị reliability
Metriks mkpuchi dị elu nwere ike izochi nnwale njikọta na-efu na nkwado oghere ọnọdụ.
Ọsọ mwepụta na-eme ka ihe egwu mụbaa
Mbugharị ngwa ngwa na-amụba ohere iwebata nlọghachi azụ nke na-agafe.
Otú Zof si egbochi mkpọchi
Ụzọ doro anya, nke usoro iji jide nlọghachi azụ tupu ha eru na mmepụta.
Mapụta usoro ọrụ dị oké mkpa na ndabere
Zof na-ewu System Graph nke gburugburu gị: ọrụ, API, mmụba data, na njikọta. Mgbe a na-eme mgbanwe, ọ maara kpọmkwem ihe nwere ike imetụta.
Bunye ndị nnọchiteanya nkwado pụrụ iche
Ihe karịrị ndị nnọchiteanya AI 100+ na-anwale akụkụ niile: izi ezi ọrụ, arụmọrụ, nchekwa, dakọtara, na ahụike njikọta. Onye nnọchiteanya ọ bụla bụ ọkachamara na ngalaba ya.
Kpalite mgbe niile (PR, mbubata, oge)
Arịrịọ mmịnye ọ bụla, ntinye ọ bụla, ọsọ a haziri ọ bụla na-enweta nkwado. A na-ejide nsogbu n'ime nkeji, ọ bụghị mgbe mbugharị gasịrị.
Jide nlọghachi azụ n'ofe UI, API, njikọta
Ndị nnọchiteanya na-enyocha usoro ọrụ njedebe ruo njedebe, nkwekọrịta API, njikọta ndị nke atọ, na usoro chere ihu ojiji. Ọ dịghị ihe na-agafe.
Gbochie mwepụta dị ize ndụ tupu mmetụta
Mgbe nkwado dara, a na-egbochi mwepụta na-akpaghị aka. Ndị otu injinia na-enweta nzaghachi doro anya, nke a ga-arụ ọrụ iji dozie nsogbu tupu mmepụta.
Loop mgbochi mkpọchi
Nkwado na-aga n'ihu na-egbochi mwepụta tupu mmetụta mmepụta.
Nsonaazụ ụlọ ọrụ dị mkpa
Metriks na ikike na-egosi mmụba reliability na ndabere nzukọ.
Ruo 95%
Ihe mberede mmepụta pere mpe
Jide nlọghachi azụ tupu mbugharị, na-ebelata ihe mberede mmepụta ma na-eme ka metriks DORA ka mma.
Ruo 90%
Usoro mwepụta dị ngwa
Ọnụ ụzọ nkwado akpaghị aka na-enyere aka mwepụta nwere ntụkwasị obi n'ebelataghị ọsọ mbugharị.
Enwere ike ịtụle
Mbelata n'ibu oku-na-oge
Nkwado mgbochi na-ebelata ịgbanyụ ọkụ, na-eme ka ndị otu injinia lekwasị anya n'iwu ihe.
Oge-mgbe-niile
Dashboard reliability
Nhụta zuru ezu n'ime metriks reliability na mkpuchi nkwado maka mkpesa ndị ndu.
Ebe nke a dabara na ngwa gị
Zof na-agbakwunye akụkụ mgbochi na-efu na ngwa reliability dị gị adị.
CI/CD
Jikọọ na GitHub Actions, GitLab CI, Jenkins, na paịpụlaịnị ndị ọzọ iji gbochie mwepụta na-akpaghị aka.
Nhụta
Mejupụta Datadog, New Relic, na ngwaọrụ nlekota ndị ọzọ na nkwado mgbochi tupu mmepụta.
Njikwa ihe mberede
Belata ihe mberede na-abanye na PagerDuty, Opsgenie, na ikpo okwu ndị yiri ya site n'ijide nsogbu n'oge.
Ịnweta tiketi
Jikọọ na Jira, Linear, na sistemu ndị ọzọ iji mepụta tiketi na-akpaghị aka mgbe nkwado dara.
Dị njikere maka ụlọ ọrụ ma tụkwasịkwa obi
Ewuru maka nzukọ chọrọ nchekwa, nnabata, na ọrụ magburu onwe.
Ọnọdụ nchekwa
SOC 2 Type II, na-agbaso GDPR, na njikwa SOC 2 Type II na GDPR.
Njikwa ohere na ọchịchị
Njikwa ohere dabere na ọrụ, ndekọ nyocha, na mkpesa nnabata.
Mbanye ụlọ ọrụ
Nkwado raara onwe ya nye, njikọta omenala, na nhọrọ mbugharị ahaziri ahazi.
Nkwado
Nkwado 24/7, SLA, na ih ịga nke ọma ndị ahịa raara onwe ya nye maka ndị ahịa ụlọ ọrụ.
Reliability sessions
Preventing outages with continuous validation and pipeline visibility.
1:00Enterprise QAScaling Quality Assurance for Enterprise
How AI-powered testing fleets scale enterprise software validation, expanding coverage, accelerating releases, and preventing production incidents with quality intelligence and release confidence.
Watch session
0:54Reliability OperationsRestoring Engineering Velocity
Explore the hidden reliability bottlenecks slowing engineering teams and how quality intelligence with testing fleets restores velocity through evidence-based validation and governed remediation.
Watch session
Kwụsị mkpọchi tupu ha amalite
Lee otú Zof si egbochi ọdịda mmepụta ma na-echekwa ego gị, aha gị, na ọsọ injinia.
Ndị metụtara
Nyochaa ikike na ngwọta ndị metụtara