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Mit anderen Worten: In der Testumgebung läuft alles „schön sauber“, aber in der Realität kommen ganz andere Faktoren\nins Spiel.",{"type":29,"tag":48,"props":14761,"children":14762},{},[14763,14767],{"type":29,"tag":52,"props":14764,"children":14765},{},[14766],{"type":56,"value":14716},{"type":56,"value":14768}," Entwickler und Kunden haben oft nicht den vollständigen Überblick über reale Anwendungsfälle, Edge-Cases und\nLastspitzen.",{"type":29,"tag":48,"props":14770,"children":14771},{},[14772,14774,14779,14781,14786,14788,14792,14794,14799],{"type":56,"value":14773},"Entwicklungsteams und selbst die Kunden kennen zwar die ",{"type":29,"tag":14566,"props":14775,"children":14776},{},[14777],{"type":56,"value":14778},"Hauptanwendungsfälle",{"type":56,"value":14780}," ihrer Software, doch ",{"type":29,"tag":52,"props":14782,"children":14783},{},[14784],{"type":56,"value":14785},"reale Benutzer",{"type":56,"value":14787},"\ntreiben Anwendungen gerne an ihre Grenzen. Plötzlich nutzen sie Features in Kombinationen, an die niemand gedacht hat,\noder geben unerwartete Daten ein. Solche ",{"type":29,"tag":52,"props":14789,"children":14790},{},[14791],{"type":56,"value":14636},{"type":56,"value":14793}," (Rand- oder Grenzfälle) bleiben in der Spezifikation oft\nunentdeckt. Erst im Echtbetrieb tauchen dann Fehler auf, die vorher niemand vorausgesehen hat. Ein Grund dafür ist,\ndass einige Bugs nur unter spezifischen Bedingungen auftreten, die man in Pre-Production-Tests nicht antizipiert.\nBeispielsweise könnte ein Nutzerprofil mit einem ",{"type":29,"tag":14566,"props":14795,"children":14796},{},[14797],{"type":56,"value":14798},"Emoji",{"type":56,"value":14800}," im Namen irgendwo in der Verarbeitung einen Fehler auslösen –\netwas, das im Testdatensatz nicht vorkam. Oder ein Kunde nutzt die Web-App auf einem älteren Browser und stößt auf\nDarstellungsprobleme. Solche Fälle zeigen sich oft erst, wenn die Anwendung „in freier Wildbahn“ verwendet wird.",{"type":29,"tag":48,"props":14802,"children":14803},{},[14804,14806,14811,14813,14818,14820,14825,14827,14832,14834,14839],{"type":56,"value":14805},"Zudem kennen Kunden zwar ihre Geschäftsprozesse, aber ",{"type":29,"tag":52,"props":14807,"children":14808},{},[14809],{"type":56,"value":14810},"Lastspitzen",{"type":56,"value":14812}," durch Marketing-Aktionen oder völlig atypische\nNutzungszeiten (z.B. am Wochenende um 3 Uhr nachts) werden leicht unterschätzt. Die ",{"type":29,"tag":52,"props":14814,"children":14815},{},[14816],{"type":56,"value":14817},"kritische Perspektive",{"type":56,"value":14819}," hier:\nModerne Ansätze versuchen diese Lücken zu schließen und propagieren, dass Entwicklungs- und Produktionsumgebung so\nähnlich wie möglich sein sollen (",{"type":29,"tag":14566,"props":14821,"children":14822},{},[14823],{"type":56,"value":14824},"dev/prod parity",{"type":56,"value":14826},"), um spätere Überraschungen zu minimieren.\n",{"type":29,"tag":52,"props":14828,"children":14829},{},[14830],{"type":56,"value":14831},"Containerisierung",{"type":56,"value":14833}," (z.B. mit Docker) erlaubt es, lokal eine Umgebung zu schaffen, die zumindest in den\nAbhängigkeiten und Voraussetzungen der Software-Faktoren der Produktionsumgebung sehr nahekommt. Dennoch bleibt es\nillusorisch, wirklich ",{"type":29,"tag":52,"props":14835,"children":14836},{},[14837],{"type":56,"value":14838},"alle",{"type":56,"value":14840}," realen Bedingungen vorwegzunehmen.",{"type":29,"tag":48,"props":14842,"children":14843},{},[14844,14848],{"type":29,"tag":52,"props":14845,"children":14846},{},[14847],{"type":56,"value":14716},{"type":56,"value":14849}," Verhalten unter Dauerlast, externen Crawlern, Penetration-Tests oder Spam-Bots sind schwer simulierbar.",{"type":29,"tag":48,"props":14851,"children":14852},{},[14853,14855,14860,14862,14867,14869,14874,14876,14881],{"type":56,"value":14854},"Performance-Tests gehören zwar zum guten Ton, aber ",{"type":29,"tag":52,"props":14856,"children":14857},{},[14858],{"type":56,"value":14859},"dauerhafte Last 24/7",{"type":56,"value":14861}," über Wochen hinweg lässt sich „im Labor“\nkaum vollständig nachstellen. Viele Unternehmen führen vor einem Launch Stresstests durch – doch diese laufen oft nur\nwenige Stunden oder Tage. Wie sich die Anwendung über Monate verhält (Memory Leaks? Datenbank wächst unvorhergesehen?\nLogs füllen die Festplatte?) bleibt offen. Auch ",{"type":29,"tag":52,"props":14863,"children":14864},{},[14865],{"type":56,"value":14866},"böswillige Zugriffe",{"type":56,"value":14868}," sind ein Thema. Externe ",{"type":29,"tag":52,"props":14870,"children":14871},{},[14872],{"type":56,"value":14873},"Crawler",{"type":56,"value":14875}," (z.B. von\nGoogle, Bing, oder sonstigen) könnten massenhaft Seiten aufrufen oder ",{"type":29,"tag":52,"props":14877,"children":14878},{},[14879],{"type":56,"value":14880},"Spam-Bots",{"type":56,"value":14882}," atypische Eingaben und Aufrufe\nverursachen. Ein Dauerbeschuss durch ein Penetration-Testing-Tool oder gar eine echte Angriffssimulation (Stichwort\nDDoS) ist nur begrenzt machbar, ohne die echten Systeme evtl. zu gefährden oder für den Tagesbetrieb unbrauchbar zu\nmachen.",{"type":29,"tag":48,"props":14884,"children":14885},{},[14886,14888,14893,14895,14900],{"type":56,"value":14887},"Die Community der Entwickler und Dev-Ops ist sich hier einig: Es ist ",{"type":29,"tag":52,"props":14889,"children":14890},{},[14891],{"type":56,"value":14892},"unheimlich schwierig, Produktionslast wirklich zu\nsimulieren",{"type":56,"value":14894},". Selbst mit Testumgebungen, die der Prod-Umgebung ähneln, können unvorhergesehene Effekte auftreten. Ein\ninteressanter Ansatz ist dabei beinahe kontraintuitiv: Manchmal nutzt man ",{"type":29,"tag":52,"props":14896,"children":14897},{},[14898],{"type":56,"value":14899},"absichtlich unterdimensionierte\nTestumgebungen",{"type":56,"value":14901},", um Schwachstellen zu entdecken. In dem erwähnten Bericht führte eine kleine Test-Datenbank dazu, dass\nein wachsendes Log schneller die Platte füllte – ein Problem, das in einer großen Umgebung erst viel später aufgefallen\nwäre.",{"type":29,"tag":48,"props":14903,"children":14904},{},[14905,14906,14911,14913,14918,14920,14925,14927,14932,14934,14942,14943,14948,14954],{"type":56,"value":6227},{"type":29,"tag":52,"props":14907,"children":14908},{},[14909],{"type":56,"value":14910},"überwiegende Meinung",{"type":56,"value":14912}," in der Tech-Community ist jedoch, dass ",{"type":29,"tag":52,"props":14914,"children":14915},{},[14916],{"type":56,"value":14917},"nichts an echte Produktions-Tests herankommt",{"type":56,"value":14919},".\nGroße Player wie Netflix propagieren sogar ",{"type":29,"tag":14566,"props":14921,"children":14922},{},[14923],{"type":56,"value":14924},"Chaos Engineering",{"type":56,"value":14926},", bei dem in der laufenden Produktion gezielt Störungen\nerzeugt werden, um die Systemrobustheit zu prüfen. Ein Experte fasst es so zusammen: ",{"type":29,"tag":14566,"props":14928,"children":14929},{},[14930],{"type":56,"value":14931},"„Um effektiv zu testen, muss das\nSystem in Produktion laufen. Schließlich kann man erst",{"type":56,"value":14933}," ",{"type":29,"tag":14566,"props":14935,"children":14936},{},[14937],{"type":29,"tag":52,"props":14938,"children":14939},{},[14940],{"type":56,"value":14941},"in Produktion",{"type":56,"value":14933},{"type":29,"tag":14566,"props":14944,"children":14945},{},[14946],{"type":56,"value":14947},"mit Faktoren wie Zustandsdaten, echten\nInputs und dem Verhalten externer Systeme arbeiten“",{"type":29,"tag":645,"props":14949,"children":14951},{"href":14950},"https://www.techtarget.com/searchsoftwarequality/tip/9-techniques-for-fixing-bugs-in-production#:~:text=want%20it%20to%2C%20and%20code,and%20how%20external%20systems%20behave",[14952],{"type":56,"value":14953},"techtarget.com",{"type":56,"value":14955},"\n. Das heißt, einige Fehler werden wir erst sehen, wenn wir live gehen. Wichtig ist dann, schnell reagieren zu können –\nund genau hier setzt DevOps an.",{"type":29,"tag":90,"props":14957,"children":14959},{"id":14958},"nach-dem-launch-ist-vor-dem-launch-analyse-und-optimierung-im-laufenden-betrieb",[14960],{"type":56,"value":14961},"Nach dem Launch ist vor dem Launch: Analyse und Optimierung im laufenden Betrieb",{"type":29,"tag":48,"props":14963,"children":14964},{},[14965,14969],{"type":29,"tag":52,"props":14966,"children":14967},{},[14968],{"type":56,"value":14716},{"type":56,"value":14970}," Weitergehende Analyse und Optimierung nach dem Launch ist essenziell.",{"type":29,"tag":48,"props":14972,"children":14973},{},[14974,14976,14980,14982,14987,14989,14994,15000],{"type":56,"value":14975},"Früher galt ein Software-Projekt mit dem Go-Live als abgeschlossen – heute weiß man, dass ",{"type":29,"tag":52,"props":14977,"children":14978},{},[14979],{"type":56,"value":14649},{"type":56,"value":14981},"\n(kontinuierliche Verbesserung) ein zentraler Bestandteil erfolgreicher Software ist. Gerade ",{"type":29,"tag":52,"props":14983,"children":14984},{},[14985],{"type":56,"value":14986},"nach dem Launch",{"type":56,"value":14988}," beginnt\ndie Phase, in der echte Nutzungsdaten ausgewertet, Engpässe erkannt und Optimierungen ausgerollt werden. So betont ein\nFachartikel: ",{"type":29,"tag":14566,"props":14990,"children":14991},{},[14992],{"type":56,"value":14993},"„Selbst mit gründlichem Pre-Launch-Testing können echte Anwender in der Praxis Performance-Probleme\naufdecken, die während der Entwicklung nicht offensichtlich waren. Post-Launch-Monitoring hilft, diese Probleme zu\nidentifizieren, bevor sie eine große Zahl von Nutzern beeinträchtigen“",{"type":29,"tag":645,"props":14995,"children":14997},{"href":14996},"https://www.topdevelopers.co/blog/post-launch-support-in-software-development/#:~:text=Even%20with%20rigorous%20pre,a%20large%20number%20of%20users",[14998],{"type":56,"value":14999},"topdevelopers.co",{"type":56,"value":15001},"\n. Anders ausgedrückt: Ein Launch ohne anschließende Überwachung ist wie die Jungfernfahrt ohne jemanden am Steuerrad.\nIn der Praxis unterschätzen gerade kleinere und mittelständische Unternehmen diesen Aufwand gern.",{"type":29,"tag":48,"props":15003,"children":15004},{},[15005,15010,15012,15017,15019,15024,15026,15031,15033,15038,15040,15045],{"type":29,"tag":52,"props":15006,"children":15007},{},[15008],{"type":56,"value":15009},"Kritische Perspektive:",{"type":56,"value":15011}," Manche denken, eine gute Software würde „out of the box“ laufen – doch das ist nach unserer\nErfahrung nur extrem selten der Fall. Es braucht Zeit und iterative Verbesserungen, um eine (Web-)Anwendung zu\n",{"type":29,"tag":52,"props":15013,"children":15014},{},[15015],{"type":56,"value":15016},"stabilisieren und zu beschleunigen",{"type":56,"value":15018},". Studien zeigen, dass ",{"type":29,"tag":14566,"props":15020,"children":15021},{},[15022],{"type":56,"value":15023},"kontinuierliche Pflege",{"type":56,"value":15025}," die ",{"type":29,"tag":52,"props":15027,"children":15028},{},[15029],{"type":56,"value":15030},"Nutzerzufriedenheit und\n-bindung",{"type":56,"value":15032}," deutlich erhöhten kann. Dazu gehören regelmäßige ",{"type":29,"tag":52,"props":15034,"children":15035},{},[15036],{"type":56,"value":15037},"Bugfixes",{"type":56,"value":15039},", Performance-Tuning (z.B. Caching-Strategien anpassen, Datenbank-Indices\noptimieren) und auch ",{"type":29,"tag":52,"props":15041,"children":15042},{},[15043],{"type":56,"value":15044},"Security-Patches",{"type":56,"value":15046},". Gerade Sicherheitslücken, die erst nach und nach publik werden, müssen sofort\ngeschlossen werden, um Schaden abzuwenden.",{"type":29,"tag":48,"props":15048,"children":15049},{},[15050,15052,15057,15059,15064,15066,15071],{"type":56,"value":15051},"Ein weiterer Aspekt ist die ",{"type":29,"tag":52,"props":15053,"children":15054},{},[15055],{"type":56,"value":15056},"Feedback-Schleife",{"type":56,"value":15058},": Durch echtes Nutzer-Feedback erfährt man, welche Features gut\nankommen und wo eventuell Usability-Probleme bestehen. Dieses Feedback fließt idealerweise direkt ins Backlog des\nEntwicklungsteams ein. Eine Kultur der ",{"type":29,"tag":14566,"props":15060,"children":15061},{},[15062],{"type":56,"value":15063},"Continuous Deployment",{"type":56,"value":15065}," stellt sicher, dass Verbesserungen zeitnah zu den Kunden\ngelangen und nicht bis zum nächsten großen „Release“ aufgeschoben werden. Moderne DevOps-Teams betrachten ihre Software\nals lebendiges Produkt: ",{"type":29,"tag":14566,"props":15067,"children":15068},{},[15069],{"type":56,"value":15070},"„Software endet nicht mit dem Launch – sie sollte als lebendiges Produkt gesehen werden.\nPost-Launch-Support ermöglicht kontinuierliche Verbesserung anhand von Nutzerfeedback und Performance-Daten“",{"type":56,"value":1651},{"type":29,"tag":48,"props":15073,"children":15074},{},[15075,15076,15081,15083,15088,15090,15095],{"type":56,"value":6227},{"type":29,"tag":52,"props":15077,"children":15078},{},[15079],{"type":56,"value":15080},"aktuelle Praxis",{"type":56,"value":15082}," in erfolgreichen Unternehmen zeigt klar: Nach dem Launch ist vor dem Launch. ",{"type":29,"tag":52,"props":15084,"children":15085},{},[15086],{"type":56,"value":15087},"Stagnation",{"type":56,"value":15089}," ist\ngefährlich – wer nach dem Go-Live nicht in ",{"type":29,"tag":52,"props":15091,"children":15092},{},[15093],{"type":56,"value":15094},"Monitoring, Fehlerbehebung und Optimierung",{"type":56,"value":15096}," investiert, riskiert Ausfälle,\nunzufriedene Nutzende und veraltete Software. Für Mittelständler bedeutet das konkret, genügend Ressourcen für die\nBetriebsphase einzuplanen oder einen kompetenten Partner zu haben, der das Monitoring und die Wartung übernimmt.",{"type":29,"tag":90,"props":15098,"children":15100},{"id":15099},"monitoring-und-logging-ohne-beobachtung-geht-es-nicht",[15101],{"type":56,"value":15102},"Monitoring und Logging: Ohne Beobachtung geht es nicht",{"type":29,"tag":48,"props":15104,"children":15105},{},[15106,15110],{"type":29,"tag":52,"props":15107,"children":15108},{},[15109],{"type":56,"value":14716},{"type":56,"value":15111}," Monitoring-Tools wie Sentry oder Grafana sind unerlässlich für Logging und Fehleranalyse.",{"type":29,"tag":48,"props":15113,"children":15114},{},[15115,15117,15122,15124,15131,15132,15139,15141,15144],{"type":56,"value":15116},"Um im laufenden Betrieb Probleme schnell zu erkennen, sind ",{"type":29,"tag":52,"props":15118,"children":15119},{},[15120],{"type":56,"value":15121},"Monitoring- und Logging-Tools",{"type":56,"value":15123}," absolut entscheidend. Zwei\nprominente Vertreter sind ",{"type":29,"tag":645,"props":15125,"children":15126},{"href":14654},[15127],{"type":29,"tag":52,"props":15128,"children":15129},{},[15130],{"type":56,"value":14660},{"type":56,"value":9692},{"type":29,"tag":645,"props":15133,"children":15134},{"href":14665},[15135],{"type":29,"tag":52,"props":15136,"children":15137},{},[15138],{"type":56,"value":14671},{"type":56,"value":15140}," (oft in Kombination mit Time-Series-Datenbanken wie Prometheus oder\nLog-Datenbanken wie ElasticSearch/Loki).\n",{"type":29,"tag":1670,"props":15142,"children":15143},{},[],{"type":29,"tag":1670,"props":15145,"children":15146},{},[],{"type":29,"tag":810,"props":15148,"children":15149},{},[15150,15201],{"type":29,"tag":814,"props":15151,"children":15152},{},[15153,15160,15162,15167,15169,15174,15176,15185,15187,15192,15194,15199],{"type":29,"tag":645,"props":15154,"children":15155},{"href":14654},[15156],{"type":29,"tag":52,"props":15157,"children":15158},{},[15159],{"type":56,"value":14660},{"type":56,"value":15161}," ist ein spezialisiertes Tool für ",{"type":29,"tag":52,"props":15163,"children":15164},{},[15165],{"type":56,"value":15166},"Error Tracking",{"type":56,"value":15168},". Es fängt Fehler und Exceptions der Anwendung ab und\nsammelt sie zentral. Warum ist das wichtig? In Produktion kann ein Entwickler nicht einfach mit dem Debugger am Code\nhängen. Sentry schließt diese Lücke: Es liefert detaillierte Fehlerreports (mit Stacktrace, User-Informationen,\nKontextvariablen etc.), sobald irgendwo im Code eine Exception auftritt. In der Dev-Community gilt Sentry daher\nmittlerweile als ",{"type":29,"tag":52,"props":15170,"children":15171},{},[15172],{"type":56,"value":15173},"industrieller Standard",{"type":56,"value":15175},", wenn es um Crash-Reporting geht\n",{"type":29,"tag":645,"props":15177,"children":15179},{"href":15178},"https://medium.com/@AndrzejSala/efficient-error-tracking-with-sentry-e975c186947c#:~:text=Sentry%20is%20a%20crash,an%20industry%20standard%20by%20TechRadar",[15180,15182],{"type":56,"value":15181},"medium.com",{"type":29,"tag":1670,"props":15183,"children":15184},{},[],{"type":56,"value":15186},".\nSelbst weniger erfahrene Entwickler finden mit Sentry schneller die Ursache von Fehlern, weil das Tool viel manuelle\nDetektivarbeit abnimmt. Ohne ein Tool wie Sentry bekommt man viele Fehler in einer komplexen Web-Anwendung gar nicht\nmit, bis Nutzende sich beschweren. Mit Sentry hingegen erfährt das Team oft ",{"type":29,"tag":52,"props":15188,"children":15189},{},[15190],{"type":56,"value":15191},"sofort",{"type":56,"value":15193},", wenn irgendwo ein Fehler\npassiert – und kann proaktiv reagieren, ",{"type":29,"tag":52,"props":15195,"children":15196},{},[15197],{"type":56,"value":15198},"bevor",{"type":56,"value":15200}," alle Nutzenden betroffen sind.",{"type":29,"tag":814,"props":15202,"children":15203},{},[15204,15211,15213,15218,15220,15225,15227,15232,15234,15239,15241,15246,15248,15253,15255,15260,15262,15267],{"type":29,"tag":645,"props":15205,"children":15206},{"href":14665},[15207],{"type":29,"tag":52,"props":15208,"children":15209},{},[15210],{"type":56,"value":14671},{"type":56,"value":15212}," dagegen adressiert das ",{"type":29,"tag":52,"props":15214,"children":15215},{},[15216],{"type":56,"value":15217},"Performance-Monitoring und die Visualisierung",{"type":56,"value":15219}," von Systemmetriken. Grafana\nselbst ist eigentlich ein Dashboard-Werkzeug, das verschiedene Datenquellen einbinden kann – von Server-CPU-Auslastung\nüber Datenbank-Performance bis hin zu anwendungsspezifischen KPIs. In Kombination mit z.B. ",{"type":29,"tag":52,"props":15221,"children":15222},{},[15223],{"type":56,"value":15224},"Prometheus",{"type":56,"value":15226}," (für\nMetrik-Sammlung) oder ",{"type":29,"tag":52,"props":15228,"children":15229},{},[15230],{"type":56,"value":15231},"Loki",{"type":56,"value":15233}," (für Log-Sammlung) entsteht so ein mächtiges ",{"type":29,"tag":52,"props":15235,"children":15236},{},[15237],{"type":56,"value":15238},"Monitoring-Cockpit",{"type":56,"value":15240},". Man möchte ",{"type":29,"tag":14566,"props":15242,"children":15243},{},[15244],{"type":56,"value":15245},"auf\neinen Blick",{"type":56,"value":15247}," sehen können, ob alle Systeme grün sind, wo vielleicht Engpässe drohen oder ob ungewöhnliche Ausschläge\nauftreten. Konkret bedeutet dies: Grafana & Co. helfen dabei, ",{"type":29,"tag":52,"props":15249,"children":15250},{},[15251],{"type":56,"value":15252},"Trends",{"type":56,"value":15254}," zu erkennen (z.B. stetig steigende\nSpeicherlast), ",{"type":29,"tag":52,"props":15256,"children":15257},{},[15258],{"type":56,"value":15259},"Anomalien",{"type":56,"value":15261}," aufzuspüren (z.B. plötzlicher Traffic-Anstieg um Mitternacht) und im Fehlerfall schnell\ndie ",{"type":29,"tag":52,"props":15263,"children":15264},{},[15265],{"type":56,"value":15266},"Ursache einzugrenzen",{"type":56,"value":1651},{"type":29,"tag":1670,"props":15269,"children":15270},{},[],{"type":29,"tag":15272,"props":15273,"children":15274},"icons-dev-ops",{},[],{"type":29,"tag":48,"props":15276,"children":15277},{},[15278,15282,15284,15289,15291,15296,15298,15303,15305,15310,15312,15317],{"type":29,"tag":52,"props":15279,"children":15280},{},[15281],{"type":56,"value":15009},{"type":56,"value":15283}," Braucht jede kleinere Web-Anwendung gleich so ein Arsenal an Tools? Einige kleinere\nUnternehmen versuchen zunächst, ohne dediziertes Monitoring auszukommen, und verlassen sich auf einfache Logs oder\nmanuelles Überprüfen. Unsere persönliche Erfahrung zeigt jedoch: ",{"type":29,"tag":52,"props":15285,"children":15286},{},[15287],{"type":56,"value":15288},"Spätestens beim ersten größeren Problem wird klar,\ndass Monitoring kein „nice-to-have“, sondern ein echter Mehrwert",{"type":56,"value":15290}," ist. Ohne diese Tools tappt man schnell und lange im\nDunkeln und wühlt sich durch Log-Dateien. Essentiell ist jedoch, die ",{"type":29,"tag":52,"props":15292,"children":15293},{},[15294],{"type":56,"value":15295},"Flut an Daten",{"type":56,"value":15297}," richtig zu kanalisieren und dann\nzu interpretieren. Monitoring richtig aufzusetzen kostet anfangs Zeit (und erfordert etwas Expertise), zahlt sich aber\nbeim ersten Incident vielfach aus. Ein gut konfiguriertes Monitoring vermeidet zudem ",{"type":29,"tag":14566,"props":15299,"children":15300},{},[15301],{"type":56,"value":15302},"Alert Fatigue",{"type":56,"value":15304}," – also zu viele\nFehlalarme. Hier ist ",{"type":29,"tag":52,"props":15306,"children":15307},{},[15308],{"type":56,"value":15309},"Qualität vor Quantität",{"type":56,"value":15311}," gefragt. Lieber wenige, dafür aussagekräftige Metriken und Alerts. Wir\nraten allen unseren Kunden mit Nachdruck: ",{"type":29,"tag":14566,"props":15313,"children":15314},{},[15315],{"type":56,"value":15316},"die Investition in Monitoring- und Logging-Tools sind unerlässlich",{"type":56,"value":15318},", um im\nFehlerfall handlungsfähig zu bleiben!",{"type":29,"tag":90,"props":15320,"children":15322},{"id":15321},"automatische-alerts-zabbix-und-co-als-wächter-der-systeme",[15323],{"type":56,"value":15324},"Automatische Alerts: Zabbix und Co. als Wächter der Systeme",{"type":29,"tag":48,"props":15326,"children":15327},{},[15328,15332],{"type":29,"tag":52,"props":15329,"children":15330},{},[15331],{"type":56,"value":14716},{"type":56,"value":15333}," Überwachungstools wie Zabbix sind notwendig für Alerts bei kritischen Systemzuständen.",{"type":29,"tag":48,"props":15335,"children":15336},{},[15337,15339,15344,15346,15350,15351,15356,15357,15362,15364,15371,15373,15378,15380,15385],{"type":56,"value":15338},"Neben dem reinen Beobachten von Metriken wollen wir natürlich ",{"type":29,"tag":52,"props":15340,"children":15341},{},[15342],{"type":56,"value":15343},"automatisch alarmiert",{"type":56,"value":15345}," werden, wenn etwas aus dem Ruder\nläuft. Hier kommen Systemüberwachungs-Tools wie ",{"type":29,"tag":52,"props":15347,"children":15348},{},[15349],{"type":56,"value":385},{"type":56,"value":10187},{"type":29,"tag":52,"props":15352,"children":15353},{},[15354],{"type":56,"value":15355},"Nagios",{"type":56,"value":10187},{"type":29,"tag":52,"props":15358,"children":15359},{},[15360],{"type":56,"value":15361},"Icinga",{"type":56,"value":15363}," etc. ins Spiel. Bleiben wir bei\n",{"type":29,"tag":645,"props":15365,"children":15366},{"href":14676},[15367],{"type":29,"tag":52,"props":15368,"children":15369},{},[15370],{"type":56,"value":385},{"type":56,"value":15372},"als Beispiel: Zabbix ist ein Open-Source-Monitoring-System, das vordefinierte ",{"type":29,"tag":52,"props":15374,"children":15375},{},[15376],{"type":56,"value":15377},"Trigger",{"type":56,"value":15379}," und\n",{"type":29,"tag":52,"props":15381,"children":15382},{},[15383],{"type":56,"value":15384},"Benachrichtigungen",{"type":56,"value":15386}," bietet. Man kann Grenzwerte festlegen – z.B. „CPU-Last > 90% über 5 Minuten“ oder „weniger als 10%\nfreier Plattenplatz“ – und sobald diese erreicht sind, sendet Zabbix einen Alarm (per E-Mail, SMS, Slack usw.).",{"type":29,"tag":48,"props":15388,"children":15389},{},[15390,15392,15396,15398,15403,15405,15409,15411,15416],{"type":56,"value":15391},"Warum braucht man das, wo wir doch eben Grafana & Co. gelobt haben? Der Unterschied: ",{"type":29,"tag":52,"props":15393,"children":15394},{},[15395],{"type":56,"value":14671},{"type":56,"value":15397}," ist super für\nVisualisierung und Analyse, aber ",{"type":29,"tag":52,"props":15399,"children":15400},{},[15401],{"type":56,"value":15402},"aktive Alarmierung",{"type":56,"value":15404}," übernimmt oft ein dediziertes Tool wie Zabbix (oder Grafana wird\nmit einem Alertmanager kombiniert). ",{"type":29,"tag":52,"props":15406,"children":15407},{},[15408],{"type":56,"value":385},{"type":56,"value":15410}," und ähnliche Tools sind quasi die ",{"type":29,"tag":52,"props":15412,"children":15413},{},[15414],{"type":56,"value":15415},"Nachtwächter",{"type":56,"value":15417},", die unermüdlich auf\ndefinierte Bedingungen achten.",{"type":29,"tag":48,"props":15419,"children":15420},{},[15421,15423,15428,15434,15436,15440],{"type":56,"value":15422},"Die Wichtigkeit solcher Alerts kann man gar nicht überschätzen. Ein treffendes Zitat aus einem Linux-Journal-Artikel:\n",{"type":29,"tag":14566,"props":15424,"children":15425},{},[15426],{"type":56,"value":15427},"„Alerts und Trigger sind der Herzschlag des Monitorings. Zabbix lässt einen spezifische Bedingungen definieren, bei\nderen Eintreten Benachrichtigungen über verschiedene Kanäle versendet werden, sodass man unverzüglich über kritische\nEreignisse informiert wird“",{"type":29,"tag":645,"props":15429,"children":15431},{"href":15430},"https://www.linuxjournal.com/content/how-monitor-your-system-zabbix#:~:text=Alerts%20and%20triggers%20are%20the,that%20could%20impact%20system%20performance",[15432],{"type":56,"value":15433},"linuxjournal.com",{"type":56,"value":15435},"\n. Ohne ein Alerting-System kann es passieren, dass ein Problem stundenlang unentdeckt bleibt – im schlimmsten Fall\nerfährt man es zuerst vom verärgerten Kunden am Telefon. Mit richtig konfigurierten Alerts erfährt das Team hingegen\n",{"type":29,"tag":52,"props":15437,"children":15438},{},[15439],{"type":56,"value":15191},{"type":56,"value":15441},", wenn zum Beispiel der Webserver ausgefallen ist oder die Antwortzeiten kritisch hochgehen.",{"type":29,"tag":48,"props":15443,"children":15444},{},[15445,15450,15452,15457,15459,15464,15466,15471],{"type":29,"tag":52,"props":15446,"children":15447},{},[15448],{"type":56,"value":15449},"Praxisblick:",{"type":56,"value":15451}," Für mittelständische Unternehmen, die vielleicht kein 24/7-Betriebsteam haben, ist ein gutes Alerting\nnoch wichtiger. Es ermöglicht kleinen Teams, effizient zu arbeiten, weil sie sich auf die Warnmeldungen verlassen\nkönnen, anstatt ständig manuell alles zu überprüfen. Allerdings gilt auch hier, dass ein schlecht konfiguriertes System,\ndas andauernd „Wölfe, Wölfe, …“ schreit (Stichwort ",{"type":29,"tag":14566,"props":15453,"children":15454},{},[15455],{"type":56,"value":15456},"false positives",{"type":56,"value":15458},"), wird schnell ignoriert. Die Kunst ist,\n",{"type":29,"tag":52,"props":15460,"children":15461},{},[15462],{"type":56,"value":15463},"sinnvolle Grenzwerte",{"type":56,"value":15465}," zu definieren und ",{"type":29,"tag":52,"props":15467,"children":15468},{},[15469],{"type":56,"value":15470},"kontextreiche Alerts",{"type":56,"value":15472}," zu versenden (z.B. direkt mit Hinweis, welche\nKomponente betroffen ist, Logs anhängen etc.).",{"type":29,"tag":48,"props":15474,"children":15475},{},[15476,15483,15485,15490],{"type":29,"tag":645,"props":15477,"children":15478},{"href":14676},[15479],{"type":29,"tag":52,"props":15480,"children":15481},{},[15482],{"type":56,"value":385},{"type":56,"value":15484}," hat sich in vielen unserer Projekte bewährt und wird bei uns intern oft als ",{"type":29,"tag":52,"props":15486,"children":15487},{},[15488],{"type":56,"value":15489},"unverzichtbares Werkzeug",{"type":56,"value":15491},"\ngenannt.",{"type":29,"tag":90,"props":15493,"children":15495},{"id":15494},"cicd-pipelines-standardisierte-deployments-auch-für-anfänger",[15496],{"type":56,"value":15497},"CI/CD-Pipelines: Standardisierte Deployments – auch für Anfänger",{"type":29,"tag":48,"props":15499,"children":15500},{},[15501,15505],{"type":29,"tag":52,"props":15502,"children":15503},{},[15504],{"type":56,"value":14716},{"type":56,"value":15506}," CI/CD-Pipelines ermöglichen standardisierte, sichere Deployments auch für wenig erfahrene Entwickler.",{"type":29,"tag":48,"props":15508,"children":15509},{},[15510,15512,15516,15518,15523,15525,15530,15532,15537],{"type":56,"value":15511},"Die Begriffe ",{"type":29,"tag":52,"props":15513,"children":15514},{},[15515],{"type":56,"value":5277},{"type":56,"value":15517}," stehen für ",{"type":29,"tag":14566,"props":15519,"children":15520},{},[15521],{"type":56,"value":15522},"Continuous Integration",{"type":56,"value":15524}," (kontinuierliche Integration) und ",{"type":29,"tag":14566,"props":15526,"children":15527},{},[15528],{"type":56,"value":15529},"Continuous\nDelivery/Deployment",{"type":56,"value":15531}," (kontinuierliche Auslieferung bzw. Bereitstellung). Eine ",{"type":29,"tag":52,"props":15533,"children":15534},{},[15535],{"type":56,"value":15536},"CI/CD-Pipeline",{"type":56,"value":15538}," ist eine automatisierte\nProzesskette, die Code vom Commit bis zum Rollout durchbaut, testet und schließlich deployt. Warum ist das so wichtig –\nund wie hilft es weniger erfahrenen Entwicklern?",{"type":29,"tag":48,"props":15540,"children":15541},{},[15542,15544,15549,15551,15556],{"type":56,"value":15543},"In traditionellen Entwicklungsabläufen war das ",{"type":29,"tag":52,"props":15545,"children":15546},{},[15547],{"type":56,"value":15548},"Deployment",{"type":56,"value":15550}," oft Handarbeit, ausgeführt von erfahrenen Admins oder\nDevOps-Engineers, weil viel schiefgehen konnte (fehlende Abhängigkeiten, falsche Configs, Downtime vermeiden etc.). Mit\neiner gut eingerichteten CI/CD-Pipeline wird Deployment jedoch zu einem ",{"type":29,"tag":52,"props":15552,"children":15553},{},[15554],{"type":56,"value":15555},"standardisierten, wiederholbaren Vorgang",{"type":56,"value":15557}," –\nim Idealfall auf Knopfdruck. Selbst wenn ein Entwickler noch nie manuell einen Linux-Server eingerichtet hat, kann er\ndurch die Pipeline-Funktionalität Code live stellen, weil die Pipeline ihm die nötigen Schritte abnimmt.",{"type":29,"tag":48,"props":15559,"children":15560},{},[15561,15566,15568,15573,15575,15579,15580,15585,15587,15592],{"type":29,"tag":52,"props":15562,"children":15563},{},[15564],{"type":56,"value":15565},"Sicherheit und Qualität",{"type":56,"value":15567}," kommen dabei nicht zu kurz – im Gegenteil. Gerade weniger erfahrene Entwickler profitieren\ndavon, dass die Pipeline ",{"type":29,"tag":14566,"props":15569,"children":15570},{},[15571],{"type":56,"value":15572},"vor",{"type":56,"value":15574}," dem Deployment automatisierte ",{"type":29,"tag":52,"props":15576,"children":15577},{},[15578],{"type":56,"value":3649},{"type":56,"value":9692},{"type":29,"tag":52,"props":15581,"children":15582},{},[15583],{"type":56,"value":15584},"Code-Checks",{"type":56,"value":15586}," ausführt. So werden Fehler\nabgefangen, bevor sie auf die Nutzerschaft losgelassen werden. Zudem sorgt die Pipeline dafür, dass immer auf ",{"type":29,"tag":52,"props":15588,"children":15589},{},[15590],{"type":56,"value":15591},"die\ngleiche Weise",{"type":56,"value":15593}," deployed wird – es gibt keine Abweichungen, die durch menschliches Vergessen passieren (z.B. „Oops, die\nstaging Config auf Prod geladen“ – solche Patzer werden eliminiert). Für KMUs bedeutet das: schnellere Updates bei\ngleichzeitig geringerer Fehlerquote.",{"type":29,"tag":48,"props":15595,"children":15596},{},[15597,15599,15604,15606,15611],{"type":56,"value":15598},"Natürlich erfordert das Einrichten einer CI/CD-Pipeline zunächst ",{"type":29,"tag":52,"props":15600,"children":15601},{},[15602],{"type":56,"value":15603},"Know-how und Aufwand",{"type":56,"value":15605},". Hier kommt oft ein\nDevOps-Spezialist ins Spiel, der eine solche Pipeline (z.B. mit Jenkins, GitLab CI, GitHub Actions oder Bitbucket\nPipelines) aufbaut. ",{"type":29,"tag":52,"props":15607,"children":15608},{},[15609],{"type":56,"value":15610},"Kritisch betrachtet",{"type":56,"value":15612}," argumentieren manche, dass in einem perfekten DevOps-Team diese\nUnterscheidung zwischen Entwicklern und DevOps gar nicht mehr nötig wäre, weil alle für den Prozess verantwortlich sind.\nIn der Realität ist es aber gerade für weniger erfahrene Entwickler eine enorme Erleichterung, wenn ein robustes\nCI/CD-System existiert – es nimmt ihnen die Deployment-Angst (das gilt auch für mich selbst als\nProjekt-Verantwortlicher). Ein Junior-Entwickler kann mit ruhigem Gewissen auf „Deploy“ klicken, weil er weiß, wenn\nautomatisierte Tests durchlaufen sind und der Rollout kontrolliert abläuft, besteht ein Mindestmaß an Sicherheit, dass\ndas Produktivsystem nicht beeinträchtigt wird.",{"type":29,"tag":48,"props":15614,"children":15615},{},[15616,15618,15623,15625,15630,15632,15637],{"type":56,"value":15617},"Wichtig ist, dass CI/CD nicht nur technische, sondern auch ",{"type":29,"tag":52,"props":15619,"children":15620},{},[15621],{"type":56,"value":15622},"kulturelle Veränderungen",{"type":56,"value":15624}," mit sich bringt. Deployments\nwerden kleiner, dafür häufiger. Das reduziert Risiko und Fehler-Impact. Teams gewöhnen sich daran, dass Deployments\n",{"type":29,"tag":14566,"props":15626,"children":15627},{},[15628],{"type":56,"value":15629},"Alltag",{"type":56,"value":15631}," sind und nicht „Großkampftage“. Gerade in der ",{"type":29,"tag":52,"props":15633,"children":15634},{},[15635],{"type":56,"value":15636},"Agilen Entwicklung",{"type":56,"value":15638}," ist CI/CD quasi das Rückgrat, um schnelle\nIterationen überhaupt zu ermöglichen.",{"type":29,"tag":48,"props":15640,"children":15641},{},[15642,15644,15649],{"type":56,"value":15643},"Zusammengefasst: CI/CD-Pipelines sind ein Game-Changer, der auch weniger erfahrene Entwickler befähigt,\n",{"type":29,"tag":52,"props":15645,"children":15646},{},[15647],{"type":56,"value":15648},"auf Knopfdruck",{"type":56,"value":15650}," auszuliefern – zuverlässig und wiederholbar.",{"type":29,"tag":90,"props":15652,"children":15654},{"id":15653},"erfahrung-zählt-live-daten-spezielle-fehler-und-die-rolle-von-devops-experten",[15655],{"type":56,"value":15656},"Erfahrung zählt: Live-Daten, spezielle Fehler und die Rolle von DevOps-Experten",{"type":29,"tag":48,"props":15658,"children":15659},{},[15660,15664],{"type":29,"tag":52,"props":15661,"children":15662},{},[15663],{"type":56,"value":14716},{"type":56,"value":15665}," Bestimmte Fehler und Performance-Probleme zeigen sich nur auf Live-Daten und erfordern erfahrene\nDevOps-Spezialisten.",{"type":29,"tag":48,"props":15667,"children":15668},{},[15669,15671,15676,15678,15683,15685,15690],{"type":56,"value":15670},"Trotz aller Automatisierung und Testing bleibt die ",{"type":29,"tag":52,"props":15672,"children":15673},{},[15674],{"type":56,"value":15675},"Erfahrung",{"type":56,"value":15677}," im Umgang mit Produktionssystemen ist durch nichts zu\nersetzen. Es gibt Fehlerbilder, die erst bei echten ",{"type":29,"tag":52,"props":15679,"children":15680},{},[15681],{"type":56,"value":15682},"Live-Daten und Lasten",{"type":56,"value":15684}," auftreten – etwa aufgrund komplexer\nDatenkonstellationen oder schlichter Skalierungseffekte. Ein Query, der mit 100 Test-Datensätzen blitzschnell ist, kann\nmit 100 Millionen echten Datensätzen plötzlich zum Flaschenhals werden. Oder ein ",{"type":29,"tag":52,"props":15686,"children":15687},{},[15688],{"type":56,"value":15689},"Memory-Leak",{"type":56,"value":15691}," in einer bestimmten\nLibrary fällt erst nach Wochen Dauerbetrieb auf, wenn der Prozess immer mehr Speicher belegt. Solche Probleme zu\nerkennen und zu beheben, erfordert oft einen erfahrenen Blick.",{"type":29,"tag":48,"props":15693,"children":15694},{},[15695,15697,15702,15704,15710,15711,15717,15718,15724,15726,15731,15733,15738,15740,15745],{"type":56,"value":15696},"Ein DevOps-Engineer mit viel Betriebserfahrung hat meist ein Repertoire an ",{"type":29,"tag":52,"props":15698,"children":15699},{},[15700],{"type":56,"value":15701},"Diagnosetechniken",{"type":56,"value":15703},". Beispielsweise wissen\nerfahrene Leute, wie man mit Tools wie ",{"type":29,"tag":672,"props":15705,"children":15707},{"className":15706},[],[15708],{"type":56,"value":15709},"htop",{"type":56,"value":10187},{"type":29,"tag":672,"props":15712,"children":15714},{"className":15713},[],[15715],{"type":56,"value":15716},"iotop",{"type":56,"value":11194},{"type":29,"tag":672,"props":15719,"children":15721},{"className":15720},[],[15722],{"type":56,"value":15723},"strace",{"type":56,"value":15725}," auf Linux debuggt, was weniger routinierte Entwickler\nvielleicht nie gebraucht haben. Auch ",{"type":29,"tag":52,"props":15727,"children":15728},{},[15729],{"type":56,"value":15730},"Dauerlast-Phänomene",{"type":56,"value":15732}," (Stichwort ",{"type":29,"tag":14566,"props":15734,"children":15735},{},[15736],{"type":56,"value":15737},"Floating-Point-Precision Bugs",{"type":56,"value":15739},",\nspeicherbedingte Rounding Errors, etc.) kennen erfahrene DevOps aus der Praxis. Ein drastisches, aber reales Szenario:\nEin Speicherfehler tritt ",{"type":29,"tag":14566,"props":15741,"children":15742},{},[15743],{"type":56,"value":15744},"nur",{"type":56,"value":15746}," unter richtiger Volllast auf und nur in Kombination mit bestimmten Hardwarebedingungen –\nhier braucht es Experten, die vielleicht schon mal ähnliches gesehen haben oder wissen, wo man ansetzt.",{"type":29,"tag":90,"props":15748,"children":15750},{"id":15749},"fazit",[15751],{"type":56,"value":15752},"Fazit",{"type":29,"tag":48,"props":15754,"children":15755},{},[15756,15758,15763,15765,15770,15772,15779],{"type":56,"value":15757},"Für (Web-)Anwendungen im produktiven Einsatz sind ",{"type":29,"tag":52,"props":15759,"children":15760},{},[15761],{"type":56,"value":15762},"DevOps kein Luxus, sondern eine Notwendigkeit",{"type":56,"value":15764},".\nEntwicklungsumgebungen stoßen an Grenzen, echte Nutzer sorgen für Überraschungen, und ohne kontinuierliches Monitoring\nfliegt man blind. Mittelständische Unternehmen, die vielleicht keine riesigen IT-Abteilungen haben, können durch einen\nDevOps-Ansatz enorm profitieren. Stabilere Systeme, schnellere Reaktionszeiten bei Problemen und zufriedenere Kunden.\nAllerdings muss man bereit sein, auch nach dem Launch ",{"type":29,"tag":52,"props":15766,"children":15767},{},[15768],{"type":56,"value":15769},"Zeit und Ressourcen zu investieren",{"type":56,"value":15771},", um Daten zu analysieren\nund Verbesserungen einzuspielen. Tools wie ",{"type":29,"tag":645,"props":15773,"children":15774},{"href":14654},[15775],{"type":29,"tag":52,"props":15776,"children":15777},{},[15778],{"type":56,"value":14660},{"type":56,"value":15780},", Grafana und Zabbix bilden dabei das Rückgrat der Überwachung – sie\nliefern die nötigen Daten und Unterstützungsmechanismen. Automatisierung mittels CI/CD nimmt viel Risiko aus Deployments\nund erlaubt auch weniger erfahrenen Team-Mitgliedern, Änderungen sicher live zu bringen.",{"type":29,"tag":48,"props":15782,"children":15783},{},[15784,15786,15791],{"type":56,"value":15785},"Am Ende zeigt sich: ",{"type":29,"tag":52,"props":15787,"children":15788},{},[15789],{"type":56,"value":15790},"Menschen",{"type":56,"value":15792}," machen den Unterschied. Erfahrene DevOps-Spezialisten können knifflige Live-Probleme\nlösen und eine Brücke zwischen Entwicklern und Betrieb schlagen.",{"type":29,"tag":48,"props":15794,"children":15795},{},[15796,15801],{"type":29,"tag":52,"props":15797,"children":15798},{},[15799],{"type":56,"value":15800},"Hinweis:",{"type":56,"value":15802}," Dieser Artikel wurde auch mit Unterstützung von KI generiert (Modell: GPT-4).",{"title":7,"searchDepth":342,"depth":342,"links":15804},[15805,15806,15807,15808,15809,15810,15811,15812],{"id":14577,"depth":342,"text":14580},{"id":14705,"depth":342,"text":14708},{"id":14958,"depth":342,"text":14961},{"id":15099,"depth":342,"text":15102},{"id":15321,"depth":342,"text":15324},{"id":15494,"depth":342,"text":15497},{"id":15653,"depth":342,"text":15656},{"id":15749,"depth":342,"text":15752},{"_path":610,"_dir":515,"_draft":6,"_partial":6,"_locale":7,"title":611,"description":612,"author":170,"image":613,"releaseDate":614,"blogCategories":15814,"articleTags":15815,"tags":15816,"body":15817,"_type":346,"_id":619,"_source":348,"_file":620,"_stem":621,"_extension":351},[579,523],[617,382],[24],{"type":26,"children":15818,"toc":16360},[15819,15825,15830,15835,15851,15864,15870,15897,15915,15921,15926,15939,15952,15983,16010,16031,16085,16101,16127,16170,16199,16249,16268,16281,16324,16336,16356],{"type":29,"tag":90,"props":15820,"children":15822},{"id":15821},"wie-man-ausgewählte-domains-über-vpn-unter-linux-auflöst",[15823],{"type":56,"value":15824},"Wie man ausgewählte Domains über VPN unter Linux auflöst",{"type":29,"tag":48,"props":15826,"children":15827},{},[15828],{"type":56,"value":15829},"In der heutigen Welt nutzen mehr Menschen als je zuvor VPN-Dienste, um aus der Ferne zu arbeiten. In manchen Fällen ist\nes jedoch nicht wünschenswert, den gesamten Datenverkehr und alle Domainnamenauflösungen über die VPN-Verbindung zu\nleiten. 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Das ist ein sehr beliebter Router in Deutschland,\nder nicht nur\neinfache\nVPN-Verbindungen anbietet, sondern auch alle Hosts in seinem Netzwerk zu seinem eigenen DNS hinzufügt. Wenn Sie mit\neinem Rechner mit dem Namen ",{"type":29,"tag":672,"props":15883,"children":15885},{"className":15884},[],[15886],{"type":56,"value":15887}," workstation",{"type":56,"value":15889}," ansprechen wollen, können Sie ihn über den dns-Namen \"workstation.fritz.box\" erreichen. 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Dig ist sehr praktisch bei der Fehlersuche bei DNS-Problemen und Ihrer Einrichtung zu testen. Sie müssen es eventuell auf Ihrem System installieren. Unter Debian befindet es sich in einem Paket namens ",{"type":29,"tag":672,"props":16004,"children":16006},{"className":16005},[],[16007],{"type":56,"value":16008},"dnsutils",{"type":56,"value":1651},{"type":29,"tag":48,"props":16011,"children":16012},{},[16013,16015,16021,16023,16029],{"type":56,"value":16014},"Installieren Sie zuerst ",{"type":29,"tag":672,"props":16016,"children":16018},{"className":16017},[],[16019],{"type":56,"value":16020},"dnsmasq",{"type":56,"value":16022}," auf Ihrem Linux und bearbeiten Sie seine Konfiguration (normalerweise in ",{"type":29,"tag":672,"props":16024,"children":16026},{"className":16025},[],[16027],{"type":56,"value":16028},"/etc/dnsmasq.conf",{"type":56,"value":16030},"). 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Die alten Daten können zu einem bestimmten Zeitpunkt verworfen werden (z.B. wenn sie nicht mehr von Snapshots verwendet werden) und die Erweiterung dient der aktuellen Version der Datei.",{"type":29,"tag":90,"props":16390,"children":16392},{"id":16391},"btrfs-fragmentierung-kann-die-leistung-ihres-systems-beeinträchtigen",[16393],{"type":56,"value":16394},"BTRFS-Fragmentierung kann die Leistung Ihres Systems beeinträchtigen",{"type":29,"tag":48,"props":16396,"children":16397},{},[16398],{"type":56,"value":16399},"Sie können sich vorstellen, dass das Lesen einer Datei mit 100k+ Erweiterungen und das Hinzufügen weiterer Erweiterungen eine Menge Buchführung und Speichersuchvorgänge von Ihrem System erfordert. Diese 10 GB große Datei ist intern in 100k+ Teile zerlegt, die gesammelt werden müssen, wenn Sie die gesamte Datei lesen wollen. Dies erhöht eindeutig die Komplexität - und verringert die Leistung.",{"type":29,"tag":90,"props":16401,"children":16403},{"id":16402},"btrfs-fragmentierung-kann-große-mengen-an-speicherplatz-blockieren",[16404],{"type":56,"value":16405},"BTRFS-Fragmentierung kann große Mengen an Speicherplatz blockieren",{"type":29,"tag":48,"props":16407,"children":16408},{},[16409],{"type":56,"value":16410},"Ja, BTRFS muss die Speicherorte dieser 100k Erweiterungen irgendwo speichern, was leicht einige zusätzliche GB an belegtem Speicherplatz zu Ihrem System hinzufügen kann. Das Schlimme daran ist, dass BTRFS Ihnen das nicht mitteilt.",{"type":29,"tag":48,"props":16412,"children":16413},{},[16414,16416,16421,16423,16428,16429,16434,16436,16441,16443,16448],{"type":56,"value":16415},"Wenn Sie sehen, dass Ihr btrfs-Dateisystem ",{"type":29,"tag":52,"props":16417,"children":16418},{},[16419],{"type":56,"value":16420},"80GB",{"type":56,"value":16422}," in ",{"type":29,"tag":14566,"props":16424,"children":16425},{},[16426],{"type":56,"value":16427},"df",{"type":56,"value":9692},{"type":29,"tag":14566,"props":16430,"children":16431},{},[16432],{"type":56,"value":16433},"btrfs fi show",{"type":56,"value":16435}," verwendet, während ",{"type":29,"tag":14566,"props":16437,"children":16438},{},[16439],{"type":56,"value":16440},"du -hsx",{"type":56,"value":16442}," nur ",{"type":29,"tag":52,"props":16444,"children":16445},{},[16446],{"type":56,"value":16447},"54GB",{"type":56,"value":16449}," anzeigt, gibt es nur zwei Gründe, die mir bekannt sind: entweder Sie haben Snapshots, die alte Erweiterungen behalten - oder Sie haben eine massive Fragmentierung.",{"type":29,"tag":90,"props":16451,"children":16453},{"id":16452},"btrfs-dateisystem-defragmentieren",[16454],{"type":56,"value":16455},"BTRFS-Dateisystem defragmentieren",{"type":29,"tag":48,"props":16457,"children":16458},{},[16459],{"type":56,"value":16460},"Es ist möglich, das BTRFS-Dateisystem auf dem gesamten Dateisystem zu defragmentieren, aber das führt dazu, dass alle Snapshots die Daten duplizieren. Es verursacht auch eine Menge IO, so dass dies nichts ist, was Sie auf Ihrem Produktionsserver ohne Grund tun wollen. Es macht wirklich keinen Sinn, statische Dateien zu defragmentieren, die fast nie geändert werden.",{"type":29,"tag":90,"props":16462,"children":16464},{"id":16463},"finden-sie-die-am-meisten-fragmentierten-dateien-auf-ihrem-system",[16465],{"type":56,"value":16466},"Finden Sie die am meisten fragmentierten Dateien auf Ihrem System",{"type":29,"tag":48,"props":16468,"children":16469},{},[16470,16472,16477],{"type":56,"value":16471},"Es gibt ein Linux-Tool namens ",{"type":29,"tag":14566,"props":16473,"children":16474},{},[16475],{"type":56,"value":16476},"filefrag",{"type":56,"value":16478},", das anzeigt, aus wie vielen Fragmenten eine Datei besteht. Also dachte ich ... \"warum nicht versuchen, die am meisten fragmentierten Dateien zu finden und nur diese zu reparieren?\" Hier ist es:",{"type":29,"tag":659,"props":16480,"children":16482},{"className":15954,"code":16481,"language":15956,"meta":7,"style":7},"find / -xdev -type f| xargs filefrag 2>/dev/null | sed 's/^\\(.*\\): \\([0-9]\\+\\) extent.*/\\2 \\1/' | awk -F ' ' '$1 > 500' | sort -n -r\n",[16483],{"type":29,"tag":672,"props":16484,"children":16485},{"__ignoreMap":7},[16486],{"type":29,"tag":127,"props":16487,"children":16488},{"class":677,"line":678},[16489,16494,16499,16504,16509,16514,16519,16524,16529,16534,16539,16544,16549,16554,16558,16563,16568,16573,16578,16582,16587,16592],{"type":29,"tag":127,"props":16490,"children":16491},{"style":3033},[16492],{"type":56,"value":16493},"find",{"type":29,"tag":127,"props":16495,"children":16496},{"style":720},[16497],{"type":56,"value":16498}," /",{"type":29,"tag":127,"props":16500,"children":16501},{"style":2303},[16502],{"type":56,"value":16503}," -xdev",{"type":29,"tag":127,"props":16505,"children":16506},{"style":2303},[16507],{"type":56,"value":16508}," -type",{"type":29,"tag":127,"props":16510,"children":16511},{"style":720},[16512],{"type":56,"value":16513}," f",{"type":29,"tag":127,"props":16515,"children":16516},{"style":4942},[16517],{"type":56,"value":16518},"|",{"type":29,"tag":127,"props":16520,"children":16521},{"style":3033},[16522],{"type":56,"value":16523}," xargs",{"type":29,"tag":127,"props":16525,"children":16526},{"style":720},[16527],{"type":56,"value":16528}," filefrag",{"type":29,"tag":127,"props":16530,"children":16531},{"style":4942},[16532],{"type":56,"value":16533}," 2>",{"type":29,"tag":127,"props":16535,"children":16536},{"style":720},[16537],{"type":56,"value":16538},"/dev/null",{"type":29,"tag":127,"props":16540,"children":16541},{"style":4942},[16542],{"type":56,"value":16543}," |",{"type":29,"tag":127,"props":16545,"children":16546},{"style":3033},[16547],{"type":56,"value":16548}," sed",{"type":29,"tag":127,"props":16550,"children":16551},{"style":720},[16552],{"type":56,"value":16553}," 's/^\\(.*\\): \\([0-9]\\+\\) extent.*/\\2 \\1/'",{"type":29,"tag":127,"props":16555,"children":16556},{"style":4942},[16557],{"type":56,"value":16543},{"type":29,"tag":127,"props":16559,"children":16560},{"style":3033},[16561],{"type":56,"value":16562}," awk",{"type":29,"tag":127,"props":16564,"children":16565},{"style":2303},[16566],{"type":56,"value":16567}," -F",{"type":29,"tag":127,"props":16569,"children":16570},{"style":720},[16571],{"type":56,"value":16572}," ' '",{"type":29,"tag":127,"props":16574,"children":16575},{"style":720},[16576],{"type":56,"value":16577}," '$1 > 500'",{"type":29,"tag":127,"props":16579,"children":16580},{"style":4942},[16581],{"type":56,"value":16543},{"type":29,"tag":127,"props":16583,"children":16584},{"style":3033},[16585],{"type":56,"value":16586}," sort",{"type":29,"tag":127,"props":16588,"children":16589},{"style":2303},[16590],{"type":56,"value":16591}," -n",{"type":29,"tag":127,"props":16593,"children":16594},{"style":2303},[16595],{"type":56,"value":16596}," -r\n",{"type":29,"tag":48,"props":16598,"children":16599},{},[16600,16602,16607,16609,16613],{"type":56,"value":16601},"Sie sollten diese Liste überprüfen. Wenn es etwas mit mehr als 10k Erstreckungen gibt, ist es ein Kandidat, um als ",{"type":29,"tag":14566,"props":16603,"children":16604},{},[16605],{"type":56,"value":16606},"nodatacow",{"type":56,"value":16608}," gekennzeichnet zu werden. In meinem Fall habe ich festgestellt, dass die Fail2ban-Sqlite-Datenbank 170k Erweiterungen verwendet, was sehr viel ist! Wenn Sie Datenbankdateien mit einer hohen Fragmentierung haben, während Sie ",{"type":29,"tag":14566,"props":16610,"children":16611},{},[16612],{"type":56,"value":16606},{"type":56,"value":16614}," verwenden, ist es besser, eine \"optimize table\" auf ihnen laufen zu lassen, da dies auch die datenbankbezogene Fragmentierung von häufig neu geschriebenen Tabellen bereinigt. Wenn Sie Snapshots verwenden, stellen Sie sicher, dass Sie etwas freien Speicherplatz haben, da die Defragmentierung eine Kopie der Dateien an Ort und Stelle erstellt, während Snapshots die Freigabe der alten Version blockieren.",{"type":29,"tag":90,"props":16616,"children":16618},{"id":16617},"wenn-alles-in-ordnung-ist-können-sie-fortfahren-und-alle-dateien-in-dieser-liste-defragmentieren",[16619],{"type":56,"value":16620},"Wenn alles in Ordnung ist, können Sie fortfahren und alle Dateien in dieser Liste defragmentieren",{"type":29,"tag":659,"props":16622,"children":16624},{"className":15954,"code":16623,"language":15956,"meta":7,"style":7},"find / -xdev -type f| xargs filefrag 2>/dev/null | sed 's/^\\(.*\\): \\([0-9]\\+\\) extent.*/\\2 \\1/' |\nawk -F ' ' '$1 > 500' | cut -d ' ' -f2 2>/dev/null | xargs -r btrfs fi defrag -f 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