Metrics, logs, traces and dashboards that answer real questions.
9 items · all topics
A web application runs on Amazon EC2 instances in an Auto Scaling group behind an Application Load Balancer. Users report being logged out at random. Investigation shows that session data is held in memory on each instance, so a request routed to a different instance loses the session. Which solution fixes this while keeping the web tier horizontally scalable?
Session state held on an instance makes that instance special, which is what breaks scaling and termination. Moving sessions to a shared store such as ElastiCache or DynamoDB makes every instance interchangeable, which is the property the rest of the architecture assumes.
A product catalogue application backed by Amazon RDS shows rising read latency. Analysis shows that a small number of identical queries account for most of the load, and the underlying data changes only a few times per day. The team wants to reduce latency to single-digit milliseconds with minimal application rework. What should a solutions architect recommend?
Repeated identical reads over rarely changing data is the textbook caching case. Amazon ElastiCache serves those queries from memory in well under a millisecond, and because the data changes a few times a day, staleness is cheap to manage.
A multiplayer game server runs on Amazon EC2 instances behind Network Load Balancers in three AWS Regions. Players connect over UDP. The company needs to route each player to the lowest-latency healthy Region, to fail over within seconds if a Region becomes unhealthy, and to publish a fixed set of IP addresses that players' firewalls can allow. Which solution meets these requirements?
UDP, static IP addresses and fast regional failover all point at AWS Global Accelerator rather than CloudFront. Global Accelerator gives you anycast static IPs, carries traffic over the AWS backbone, and reroutes without waiting for DNS to expire anywhere.
An application stores orders in an Amazon DynamoDB table with a partition key of orderId. A new reporting feature must list all orders for a given customerId, sorted by order date. Running the report currently scans the entire table and is slow and expensive. What should a solutions architect recommend?
A scan means the access pattern has no index behind it. A global secondary index with customerId as its partition key and the order date as its sort key turns that scan into a query. Only a global secondary index can introduce a new partition key on an existing table.
A HorizontalPodAutoscaler targeting 70% average CPU never scales, and kubectl describe hpa shows unknown for the current metric. Which TWO conditions would cause this?
CPU-based autoscaling needs a metrics source serving the Metrics API, normally metrics-server, and it needs CPU requests on the Pods' containers, since utilisation is a percentage of the request.
A container is in CrashLoopBackOff and kubectl logs returns nothing useful because the container has just restarted. Which command shows the output from the failed run?
kubectl logs --previous returns the logs of the previous instantiation of the container, which is where the reason for the crash actually is.
A Pod writes a large volume of logs. kubectl logs returns only recent output, and the earlier lines you need are missing. Why, and what does that imply?
The kubelet rotates container logs and kubectl logs only reads the latest file. Keeping history means shipping logs off the node to a cluster-level logging system.
You are asked to find out what happened in a namespace over the last few minutes. Which command gives the most useful ordered picture, and what limitation should you expect?
kubectl get events --sort-by=.lastTimestamp gives a namespace timeline. Events are namespaced and short-lived, retained for one hour by default, so older history is simply gone.
kubectl top nodes fails with an error saying the metrics API is not available, though every node is Ready and workloads are healthy. What does that indicate?
kubectl top reads the Metrics API, which is served by metrics-server rather than by the API server itself. Without it installed there is nothing to answer, and resource usage has to come from elsewhere.