{"id":2427,"date":"2016-11-04T04:06:33","date_gmt":"2016-11-04T04:06:32","guid":{"rendered":"https:\/\/www.couchbase.com\/blog\/?p=2427"},"modified":"2023-06-23T03:07:09","modified_gmt":"2023-06-23T10:07:09","slug":"monitoring-couchbase","status":"publish","type":"post","link":"https:\/\/www.couchbase.com\/blog\/es\/monitoring-couchbase\/","title":{"rendered":"Supervisi\u00f3n de Couchbase"},"content":{"rendered":"

VISI\u00d3N GENERAL<\/p>\n

Hace varios a\u00f1os escrib\u00ed un blog que refleja c\u00f3mo muchos clientes monitorizan sus clusters de Couchbase (https:\/\/www.couchbase.com\/blog\/monitoring-couchbase-cluster<\/span><\/a>). Aunque anticuada, la informaci\u00f3n sigue siendo relevante y vamos a actualizar ese original. Las estad\u00edsticas y m\u00e9tricas descritas en esa visi\u00f3n general son a menudo consumidas por marcos de monitorizaci\u00f3n para medir la salud y el rendimiento de Couchbase para casos de uso espec\u00edficos. Desde entonces, a menudo nos encontramos con gente que nos pide ejemplos de implementaciones que consumen estas estad\u00edsticas. Normalmente, la necesidad real de los equipos de desarrollo no son marcos de monitorizaci\u00f3n m\u00e1s amplios, sino simples scripts que se pueden aprovechar. Muchas veces los equipos funcionales cruzados est\u00e1n diagnosticando problemas en entornos de \"sala de guerra\" y quieren formas sencillas de digerir eventos recientes dentro de un cl\u00faster.<\/span><\/p>\n

El objetivo aqu\u00ed no es proporcionar un modelo completo, sino esbozar una implementaci\u00f3n sencilla que consuma m\u00e9tricas de Couchbase a trav\u00e9s de nuestra API REST y herramientas de l\u00ednea de comandos. Una vez que tengamos algo en marcha que pueda digerir estas m\u00e9tricas de forma regular, necesitaremos almacenarlas en alg\u00fan lugar. En este tutorial almacenaremos estas m\u00e9tricas en un bucket de Couchbase y utilizaremos N1QL para comprender lo que ocurre en un cl\u00faster determinado. Hay otras formas de visualizar este tipo de informaci\u00f3n (https:\/\/www.couchbase.com\/blog\/2016\/march\/http-packages.couchbase.com-releases-4.5.0-dp1-couchbase-server-enterprise_4.5.0-dp1-windows_amd64.exe.md5) pero para este ejemplo nos centraremos en la monitorizaci\u00f3n de Couchbase y las consultas N1QL asociadas.<\/p>\n

DIGERIR LA INFORMACI\u00d3N<\/p>\n

Quer\u00eda ofrecer un ejemplo que fuera relevante y \u00fatil para que los equipos lo asimilaran y utilizaran. A menudo, el uso de Python es familiar para la gente y se puede implementar f\u00e1cilmente en una variedad de sistemas. Obviamente, estos mismos m\u00e9todos podr\u00edan utilizarse en shell o en cualquier otro lenguaje, pero Python parec\u00eda el m\u00e1s adecuado para un debate generalizado.<\/p>\n

El c\u00f3digo completo se encuentra aqu\u00ed ... pythonlab<\/span><\/a><\/span><\/span>\/<\/span>MonitorStats.py\u00a0<\/span>... pero recorreremos algunos de los detalles y las diferentes formas en que estamos recopilando informaci\u00f3n de Couchbase.<\/span><\/p>\n

Lo primero que necesitamos establecer es d\u00f3nde podemos encontrar los binarios locales de Couchbase, que es todo lo que binPath hace por nosotros.<\/span><\/p>\n

# binPath = \"C:Program FilesCouchbase Server\"\r\nbinPath = \"\/Applications\/couchbase-server-enterprise_4\/Couchbase Server.app\/Contents\/Resources\/couchbase-core\/bin\"\r\n# binPath = \"\/opt\/couchbase\/bin\"<\/code><\/pre>\n
La interfaz de usuario administrativa es una gran caracter\u00edstica de Couchbase y se instala por defecto en cada nodo de un cl\u00faster Couchbase; sin embargo, esta interfaz est\u00e1 dise\u00f1ada para proporcionar una visi\u00f3n de \"lo que est\u00e1 pasando ahora\" en el cl\u00faster. Las estad\u00edsticas se agregan con el tiempo por el cl\u00faster y no proporciona informaci\u00f3n granular para revisar \"lo que pas\u00f3\" en el cl\u00faster. Porque womo estamos consumiendo estad\u00edsticas que son creadas en tiempo real por el cluster de Couchbase necesitamos alg\u00fan lugar donde almacenar los resultados. Aunque podr\u00eda haber otras opciones, utilizaremos Couchbase para almacenar nuestras estad\u00edsticas hist\u00f3ricas. El cluster que usaremos para almacenar las estad\u00edsticas estar\u00e1 controlado por seedNode y seedBucket (un SDK de Couchbase s\u00f3lo necesita un nodo y el nombre del bucket para crear una conexi\u00f3n con todos los nodos de un cluster).<\/span><\/p>\n
seedNode = \"192.168.61.101\"\r\nseedBucket = \"testload\"<\/code><\/pre>\n
\u00a0Este script se ejecutar\u00eda localmente en cada nodo del cl\u00faster y capturar\u00eda un perfil estad\u00edstico de la salud de ese nodo y su visi\u00f3n del cl\u00faster. Como resultado, el cl\u00faster que estamos monitorizando se definir\u00e1 como \"localhost\" y usaremos la API REST de Couchbase para determinar el nombre del host local.<\/span><\/p>\n
clusterNode = \"localhost\"<\/code><\/pre>\n
Todo est\u00e1 dirigido por la comprensi\u00f3n de qu\u00e9 nodo se est\u00e1 ejecutando el script y cu\u00e1ntos nodos componen el cl\u00faster. Aqu\u00ed capturaremos esta informaci\u00f3n y dirigiremos la parte restante del script de monitorizaci\u00f3n.<\/p>\n
numNodes = int(commands.getoutput(\"curl -s -u Administrator:password https:\/\/\" + clusterNode + \":8091\/pools\/default |jq '.nodes | length'\"))\r\nfor i in range(0,numNodes-1):\r\n    rtn = requests.get('https:\/\/Administrator:password@' + clusterNode + ':8091\/pools\/default')\r\n    if rtn.status_code != 200:\r\n        # This means something went wrong.\r\n        print(\"oh crap \" + rtn.status_code)\r\n    z = json.loads(rtn.text)\r\n    ctr = str((json.dumps(z['nodes'][i]['thisNode'])))\r\n    #ctr = (str(commands.getoutput(\"curl -s -u Administrator:password https:\/\/\" + clusterNode + \":8091\/pools\/default |jq .nodes[\" + str(i) + \"].thisNode\")))\r\n    if ctr == \"true\":\r\n        thisNode = (str(commands.getoutput(\"curl -s -u Administrator:password https:\/\/\" + clusterNode + \":8091\/pools\/default |jq .nodes[\" + str(i) + \"].otpNode\")))\r\n        thisNode = thisNode.split(\"@\")[1]\r\n        thisNode = thisNode.split(\"\"\")[0]\r\n        #print (\"this node\" + str(thisNode))<\/code><\/pre>\n
Para el resto del script podemos consumir estad\u00edsticas espec\u00edficas de varias maneras. Aqu\u00ed sacaremos informaci\u00f3n de la utilidad cbstats de Couchbase o directamente de nuestra API REST. Aqu\u00ed usamos cbstats para obtener la utilizaci\u00f3n de memoria de un nodo y usamos un cliente REST de Python (requests) para obtener la cola de drenaje y medir c\u00f3mo est\u00e1 funcionando el cluster en la persistencia de datos en disco. Estas son algunas de las estad\u00edsticas m\u00e1s importantes a monitorizar para un cluster Couchbase.<\/p>\n
memUsed = int(commands.getoutput(binPath + '\/cbstats ' + str(thisNode) + ':11210 -b ' + clusterBucket + ' all -j |jq .mem_used'))\r\n\r\n# diskDrain = commands.getoutput(\"curl -s -u Administrator:password https:\/\/\" + seedNode + \":8091\/pools\/default\/buckets\/testload\/stats |jq .op.samples.ep_diskqueue_drain[59]\")\r\n# Drain Queue via REST API\r\nresp = requests.get('https:\/\/Administrator:password@' + str(thisNode) + ':8091\/pools\/default\/buckets\/' + clusterBucket + '\/stats')\r\nif resp.status_code != 200:\r\n    # This means something went wrong.\r\n    print(\"oh crap \" + resp.status_code)\r\na = json.loads(resp.text)\r\ndiskDrain = int((json.dumps(a['op']['samples']['ep_diskqueue_drain'][0], indent=4, separators=(',', ': '))))<\/code><\/pre>\n
El script real muestra informaci\u00f3n adicional, pero en \u00faltima instancia capturamos todo en un documento JSON y establecemos un valor TTL<\/a> durante 30 d\u00edas.<\/p>\n
json_str = {\r\n        'type': \"stats\",\r\n        'flush': flushFail,\r\n        'drain': diskDrain,\r\n        'OOM': tempOOM,\r\n        'miss': cacheMiss,\r\n        'memory': memUsed,\r\n        'operations': opsPer,\r\n        'nodes': nodeHealth\r\n    }\r\n\r\ncb.upsert(str(thisNode) + \"::\" + nowStamp, json_str, ttl=2505600)<\/code><\/pre>\n
Con los datos de monitorizaci\u00f3n en Couchbase podemos consumir cosas a trav\u00e9s de nuestro lenguaje de consulta N1QL para buscar anomal\u00edas. Los datos en s\u00ed est\u00e1n utilizando un modelo de datos de series temporales basado en una marca de tiempo; como resultado, podemos consultar cosas que suceden en el cl\u00faster y la CLAVE (meta.id) nos mostrar\u00e1 el per\u00edodo de tiempo de inter\u00e9s. Puede que tengamos que ser inteligentes con los \u00edndices necesarios para soportar el an\u00e1lisis, pero para una plataforma de lucha contra incendios es muy factible aprovechando el lenguaje de consulta N1QL de Couchbase.<\/p>\n
SELECT meta().id, operations FROM `testload` WHERE OOM = 0<\/code><\/pre>\n
CONCLUSI\u00d3N:<\/p>\n
Esto no es algo que deba ser lanzado en producci\u00f3n, pero deber\u00eda proporcionar una gu\u00eda sobre c\u00f3mo monitorizar un entorno Couchbase. Hay mucho disponible a trav\u00e9s de la interfaz REST y cbstats, todo lo cual puede ser consumido y monitoreado de manera similar.<\/p>","protected":false},"excerpt":{"rendered":"
OVERVIEW Several years ago I wrote a blog that reflects how many customers\u00a0monitor their Couchbase clusters (https:\/\/www.couchbase.com\/blog\/monitoring-couchbase-cluster). Albeit dated, the information is still relevant and we\u2019ll be updating that original. The statistics and metrics outlined in that general overview are […]<\/p>","protected":false},"author":47,"featured_media":13873,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[1816],"tags":[],"ppma_author":[9021],"class_list":["post-2427","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-couchbase-server"],"acf":[],"yoast_head":"\nMonitoring Couchbase Cluster Environment - Overview<\/title>\n<meta name=\"description\" content=\"The post focuses on how to store the metrics in a Couchbase bucket and use N1QL to understand what\u2019s happening in a given cluster.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.couchbase.com\/blog\/es\/monitoring-couchbase\/\" \/>\n<meta property=\"og:locale\" content=\"es_MX\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Couchbase Monitoring\" \/>\n<meta property=\"og:description\" content=\"The post focuses on how to store the metrics in a Couchbase bucket and use N1QL to understand what\u2019s happening in a given cluster.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.couchbase.com\/blog\/es\/monitoring-couchbase\/\" \/>\n<meta property=\"og:site_name\" content=\"The Couchbase Blog\" \/>\n<meta property=\"article:published_time\" content=\"2016-11-04T04:06:32+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2023-06-23T10:07:09+00:00\" \/>\n<meta name=\"author\" content=\"Justin Michaels, Solutions Engineer, Couchbase\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Justin Michaels, Solutions Engineer, Couchbase\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"5 minutos\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/www.couchbase.com\/blog\/monitoring-couchbase\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/www.couchbase.com\/blog\/monitoring-couchbase\/\"},\"author\":{\"name\":\"Justin Michaels, Solutions Engineer, Couchbase\",\"@id\":\"https:\/\/www.couchbase.com\/blog\/#\/schema\/person\/3953b54b90c8d9474f4d88b142db9fc5\"},\"headline\":\"Couchbase Monitoring\",\"datePublished\":\"2016-11-04T04:06:32+00:00\",\"dateModified\":\"2023-06-23T10:07:09+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/www.couchbase.com\/blog\/monitoring-couchbase\/\"},\"wordCount\":816,\"commentCount\":0,\"publisher\":{\"@id\":\"https:\/\/www.couchbase.com\/blog\/#organization\"},\"image\":{\"@id\":\"https:\/\/www.couchbase.com\/blog\/monitoring-couchbase\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2022\/11\/couchbase-nosql-dbaas.png\",\"articleSection\":[\"Couchbase Server\"],\"inLanguage\":\"es\",\"potentialAction\":[{\"@type\":\"CommentAction\",\"name\":\"Comment\",\"target\":[\"https:\/\/www.couchbase.com\/blog\/monitoring-couchbase\/#respond\"]}]},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.couchbase.com\/blog\/monitoring-couchbase\/\",\"url\":\"https:\/\/www.couchbase.com\/blog\/monitoring-couchbase\/\",\"name\":\"Monitoring Couchbase Cluster Environment - 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