{"id":4646,"date":"2025-04-17T08:48:18","date_gmt":"2025-04-17T15:48:18","guid":{"rendered":"https:\/\/www.couchbase.com\/blog\/high-availability-automatic-failover-app-services\/"},"modified":"2025-04-17T08:48:18","modified_gmt":"2025-04-17T15:48:18","slug":"high-availability-automatic-failover-app-services","status":"publish","type":"post","link":"https:\/\/www.couchbase.com\/blog\/ko\/high-availability-automatic-failover-app-services\/","title":{"rendered":"Ensuring High Availability with Automatic Failover for App Services"},"content":{"rendered":"\n

In modern applications, continuous connectivity is key\u2014especially for mobile apps relying on backend services. In this blog, we\u2019ll walk through a Python-based solution that monitors the health of your app service servers and automatically fails over to a secondary server if needed. This sample code uses HTTP health checks and WebSocket connection endpoints to ensure that your application always connects to a healthy service.<\/span><\/p>\n\n\n\n

Overview<\/h2>\n\n\n\n

The solution involves two types of endpoints:<\/span><\/p>\n\n\n\n

    \n
  1. Health check URLs<\/b>\n
      \n
    • These endpoints (e.g., <\/span>https:\/\/...\/_ping<\/code><\/span>) are polled using HTTP <\/em><\/span>HEAD<\/span><\/em> requests.<\/span><\/li>\n
    • They determine if the app service server is healthy.<\/span><\/li>\n<\/ul>\n<\/li>\n\n\n
    • Connection endpoints<\/b>\n
        \n
      • These are the WebSocket URLs (e.g., <\/span>wss:\/\/...\/primary<\/code><\/span>) that your application uses to interact with the backend.<\/span><\/li>\n
      • The active connection endpoint is updated based on the health check results.<\/span><\/li>\n<\/ul>\n<\/li>\n\n<\/ol>\n\n\n\n

        If the primary server\u2019s health check fails consecutively, the failover logic will switch the application\u2019s connection to the secondary server.<\/span><\/p>\n\n\n\n

        The code in detail<\/h2>\n\n\n\n

        Below is the complete code with inline comments and detailed explanations:<\/span><\/p>\n\n\n

        [crayon nums=”false” lang=”python” decode=”true”]import logging
        \nimport threading
        \nimport requests
        \nfrom time import sleep<\/p>\n

        # Configure logging to show time-stamped messages at INFO level.
        \nlogging.basicConfig(level=logging.INFO, format=’%(asctime)s %(levelname)s: %(message)s’)<\/p>\n

        # ————————————–
        \n# Health Check URLs (App Service Servers)
        \n# ————————————–
        \n# These URLs are used for health checking the servers by sending HEAD requests.
        \nhealth_check_urls = {
        \n\u00a0\u00a0\u00a0\u00a0“primary”: “https:\/\/XXXXXXXXXXXXXX.apps.cloud.couchbase.com:4984\/_ping”,
        \n\u00a0\u00a0\u00a0\u00a0“secondary”: “https:\/\/XXXXXXXXXXXXXX.apps.cloud.couchbase.com:4984\/_ping”
        \n}<\/p>\n

        # ————————————-
        \n# Connection Endpoints (WebSocket URLs)
        \n# ————————————-
        \n# These endpoints are what your application actually uses for connections.
        \nconnection_urls = {
        \n\u00a0\u00a0\u00a0\u00a0“primary”: “wss:\/\/XXXXXXXXXXXXXX.apps.cloud.couchbase.com:4984\/primary”,
        \n\u00a0\u00a0\u00a0\u00a0“secondary”: “wss:\/\/XXXXXXXXXXXXXX.apps.cloud.ucouchbase.com:4984\/secondary”
        \n}<\/p>\n

        # The variable `active_cluster` tracks which server is currently active.
        \nactive_cluster = “primary”<\/p>\n

        # This variable holds the actual WebSocket URL used by your application.
        \nactive_connection_url = connection_urls[active_cluster]<\/p>\n

        def is_cluster_healthy(url):
        \n\u00a0\u00a0\u00a0\u00a0“””
        \n\u00a0\u00a0\u00a0\u00a0Perform a health check using a HEAD request against the provided URL.
        \n\u00a0\u00a0\u00a0\u00a0Returns True if the response status is 200; otherwise, returns False.
        \n\u00a0\u00a0\u00a0\u00a0Logs the status code and headers for troubleshooting.
        \n\u00a0\u00a0\u00a0\u00a0“””
        \n\u00a0\u00a0\u00a0\u00a0try:
        \n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0response = requests.head(url, timeout=5)
        \n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0logging.info(f”Health Check Response for {url}”)
        \n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0logging.info(f”\u00a0 Status Code: {response.status_code}”)
        \n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0logging.info(”\u00a0 Headers:”)
        \n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0for header, value in response.headers.items():
        \n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0logging.info(f”\u00a0 \u00a0 {header}: {value}”)<\/p>\n

        \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0if response.status_code == 200:
        \n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0logging.info(f”{url} is healthy!”)
        \n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0return True
        \n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0else:
        \n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0logging.warning(f”{url} might be unhealthy or unreachable.”)
        \n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0return False
        \n\u00a0\u00a0\u00a0\u00a0except requests.exceptions.RequestException as e:
        \n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0logging.error(f”Health check failed for {url}: {e}”)
        \n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0return False<\/p>\n

        def health_check_worker():
        \n\u00a0\u00a0\u00a0\u00a0“””
        \n\u00a0\u00a0\u00a0\u00a0A background worker that checks the health of the active server every 3 seconds.
        \n\u00a0\u00a0\u00a0\u00a0If the active server fails health checks for more than 9 consecutive times,
        \n\u00a0\u00a0\u00a0\u00a0the worker attempts to switch to the other server.
        \n\u00a0\u00a0\u00a0\u00a0“””
        \n\u00a0\u00a0\u00a0\u00a0global active_cluster
        \n\u00a0\u00a0\u00a0\u00a0global active_connection_url<\/p>\n

        \u00a0\u00a0\u00a0\u00a0consecutive_failures = 0<\/p>\n

        \u00a0\u00a0\u00a0\u00a0while True:
        \n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0sleep(3)\u00a0 # Wait 3 seconds between checks.<\/p>\n

        \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0# Use the HTTP health check endpoint for the active cluster.
        \n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0current_health_url = health_check_urls[active_cluster]
        \n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0logging.info(f”Health check: Checking {active_cluster} at {current_health_url}…”)<\/p>\n

        \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0if is_cluster_healthy(current_health_url):
        \n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0consecutive_failures = 0\u00a0 # Reset counter if healthy.
        \n \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0else:
        \n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0consecutive_failures += 1
        \n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0logging.warning(f”{active_cluster} health check failed {consecutive_failures} time(s).”)<\/p>\n

        \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0# If failures exceed 9 consecutive attempts, try to fail over.
        \n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0if consecutive_failures > 9:
        \n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0logging.error(f”{active_cluster} is considered down. Attempting to fail over…”)<\/p>\n

        \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0# Determine the new active cluster.
        \n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0new_cluster = “secondary” if active_cluster == “primary” else “primary”
        \n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0new_health_url = health_check_urls[new_cluster]<\/p>\n

        \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0# Check if the new cluster is healthy.
        \n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0if is_cluster_healthy(new_health_url):
        \n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0active_cluster = new_cluster
        \n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0# Update the connection endpoint.
        \n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0active_connection_url = connection_urls[new_cluster]
        \n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0logging.warning(f”Switched active cluster to {new_cluster}.”)
        \n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0logging.warning(f”New WebSocket connection endpoint: {active_connection_url}”)
        \n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0else:
        \n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0logging.critical(“Both clusters appear to be down!”)<\/p>\n

        \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0consecutive_failures = 0\u00a0 # Reset the failure counter after the attempt.<\/p>\n

        def main():
        \n\u00a0\u00a0\u00a0\u00a0“””
        \n\u00a0\u00a0\u00a0\u00a0Main function to start the health-check worker in a background thread.
        \n\u00a0\u00a0\u00a0\u00a0Keeps the script running indefinitely until interrupted.
        \n\u00a0\u00a0\u00a0\u00a0“””
        \n\u00a0\u00a0\u00a0\u00a0thread = threading.Thread(target=health_check_worker, daemon=True)
        \n\u00a0\u00a0\u00a0\u00a0thread.start()<\/p>\n

        \u00a0\u00a0\u00a0\u00a0logging.info(“Health check worker started. Press Ctrl+C to exit.”)
        \n\u00a0\u00a0\u00a0\u00a0logging.info(f”Application will initially connect to: {active_connection_url}”)<\/p>\n

        \u00a0\u00a0\u00a0\u00a0try:
        \n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0while True:
        \n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0sleep(1)\u00a0 # Main thread remains alive.
        \n\u00a0\u00a0\u00a0\u00a0except KeyboardInterrupt:
        \n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0logging.info(“Shutting down health check script.”)<\/p>\n

        if __name__ == “__main__”:
        \n\u00a0\u00a0\u00a0\u00a0main()[\/crayon]<\/p>\n\n\n\n

        Key technical points<\/h2>\n\n\n\n
          \n
        • Health checks on App Service Servers:<\/b>
          \n<\/b>The code separates the <\/span>health-check endpoints<\/b> (used for monitoring) from the <\/span>connection endpoints<\/b> (used by your application). This allows you to check server health independently while maintaining a stable connection endpoint.<\/span><\/li>\n\n\n
        • HTTP HEAD Requests:<\/b>
          \n<\/b>Using <\/span>HEAD<\/span> requests to the<\/span>\/_ping<\/code><\/span>\u00a0endpoint minimizes data transfer while still providing status codes and headers for diagnostics.<\/span><\/li>\n\n\n
        • Background Thread:<\/b>
          \n<\/b>The <\/span>health_check_worker<\/code><\/span> runs in its own daemon thread, allowing continuous health monitoring without blocking the main application thread.<\/span><\/li>\n\n\n
        • Failover Logic:<\/b>\n
            \n
          • A counter (<\/span>consecutive_failures<\/code><\/span>) tracks consecutive failures.<\/span><\/li>\n
          • If the count exceeds a set threshold (9 failures), the script attempts a failover by checking the health of the alternate server.<\/span><\/li>\n
          • Upon a successful health check on the secondary server, the active connection endpoint is updated.<\/span><\/li>\n<\/ul>\n<\/li>\n\n\n
          • Logging:<\/b>
            \n<\/b>Detailed logging provides insights into the health check process, including HTTP response status, headers, and failover events. This aids in troubleshooting and monitoring.<\/span><\/li>\n\n<\/ul>\n\n\n\n

            Adapting for your application<\/h2>\n\n\n\n
              \n
            • You can easily translate and adapt this code to your preferred programming language such as\u00a0 Swift and Kotlin to fit your application\u2019s needs.<\/span><\/li>\n\n\n
            • You might integrate this script or logic into your <\/span>mobile code<\/b> (iOS\/Android) or a <\/span>backend service<\/b> that updates the active<\/em>\u00a0endpoint.<\/span><\/li>\n\n\n
            • If you are on iOS or Android, consider how often and where you run this code. For example, background tasks or push notifications can trigger health checks in a mobile context.<\/span><\/li>\n\n\n
            • If you have a microservice architecture, you might run this failover logic in a small service that exposes a current active URL<\/em>\u00a0to the mobile apps, so they always connect to the correct WSS endpoint.<\/span><\/li>\n\n<\/ul>\n\n\n\n

              Conclusion<\/h2>\n\n\n\n

              This sample code provides a straightforward yet powerful mechanism for ensuring high availability in applications by automatically failing over to a backup server when the primary becomes unreachable. By separating the health checks from the connection endpoints, the application ensures that it always connects to a healthy server via WebSocket.<\/span><\/p>\n\n\n\n

              In a production environment, you may need to adapt and extend the logic to suit your specific requirements, network conditions, and security policies.<\/span><\/p>\n\n\n\n

              Implementing this logic in your mobile application or backend service can greatly improve uptime and resilience, ensuring your users remain connected even during unexpected service interruptions.<\/span><\/p>\n\n\n\n

              \u00a0<\/p>\n","protected":false},"excerpt":{"rendered":"

              In modern applications, continuous connectivity is key\u2014especially for mobile apps relying on backend services. In this blog, we\u2019ll walk through a Python-based solution that monitors the health of your app service servers and automatically fails over to a secondary server if needed. This sample code uses HTTP health checks and WebSocket connection endpoints to ensure […]<\/p>\n","protected":false},"author":85152,"featured_media":4644,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"_acf":"","footnotes":""},"categories":[627,136,301,381],"tags":[514,877],"ppma_author":[812,932],"class_list":["post-4646","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-app-services","category-best-practices-and-tutorials","category-cloud","category-python","tag-high-availability","tag-websocket"],"yoast_head":"\nEnsuring High Availability with Automatic Failover for App Services<\/title>\n<meta name=\"description\" content=\"Boost app reliability with Python-based automatic failover. 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