Storage & Databases

Amazon EFS is the AWS shared file system: an NFS file share that many EC2 instances, containers and Lambda functions mount read-write at the same time, across Availability Zones, with capacity that grows and shrinks automatically.

EC2 instance store data survives a reboot but is lost on stop, hibernate, or terminate, because it lives on disks physically inside the host. EBS volumes are network-attached and persist independently of the instance lifecycle.

gp2 derives performance from size — 3 IOPS per GiB with a burst credit bucket — so you buy capacity to get speed. gp3 ships a fixed baseline at any size and lets you provision IOPS and throughput independently, usually at a lower price per GiB.

Each EBS snapshot stores only the blocks that changed since the previous snapshot, and you are billed for the unique blocks retained. Deleting a middle snapshot is safe: AWS removes only blocks no other snapshot needs, and every remaining snapshot still restores a complete volume.

EFS is reached through a per-Availability-Zone mount target — a network interface with its own security group. A hang almost always means the third AZ has no mount target, or the mount target's security group does not allow inbound TCP 2049 from the client.

The Aurora cluster endpoint always resolves to the current writer and follows failover; the reader endpoint round-robins DNS across available readers; an instance endpoint names one fixed instance. Sending everything to the cluster endpoint puts all reads on the writer while paid-for readers sit idle.

Eventually consistent reads, the DynamoDB default, may return a slightly stale copy of an item and cost half a read unit per 4 KB. Strongly consistent reads always reflect the latest acknowledged write and cost a full read unit per 4 KB.

Valkey and Redis OSS on ElastiCache add replicas, automatic failover, snapshots and authentication; Memcached has none of those but is multi-threaded and simple. Choose Memcached only for a plain, disposable, horizontally sharded key-value cache.

Aurora separates compute from storage: every instance in a cluster attaches to one shared distributed volume that keeps six copies across three Availability Zones. Replicas replay nothing — they read the pages the writer already wrote, so lag stays in milliseconds.

On-demand bills per request and absorbs spikes with no configuration, at a higher per-request price. Provisioned bills for reserved throughput and is cheaper when load is steady and well utilised, but auto scaling reacts in minutes, so sharp spikes throttle.

A bucket policy is a resource-based policy attached to the S3 bucket itself and must name a Principal. An IAM identity policy attaches to a user, group or role, and never names a Principal because the identity it is attached to is the principal.

Multipart upload splits one object into parts sent independently: CreateMultipartUpload returns an UploadId, UploadPart sends each numbered piece, CompleteMultipartUpload assembles them. Beyond the 5 GB ceiling it adds parallelism, per-part retry, and resumable uploads.

An S3 presigned URL is an object URL carrying a SigV4 signature and an expiry in its query string. Whoever holds it performs one specific operation on one specific object using the signing principal's permissions, with no AWS credentials of their own.

An S3 Lifecycle configuration is a set of bucket-level rules that act on objects automatically as they age. A rule takes one of two kinds of action: transition an object to a cheaper storage class, or expire (delete) it.

S3 erases nothing: it adds a delete marker as the new current version, so plain GETs return 404 while every earlier version stays stored and billed. You restore by deleting the delete marker by its own version ID.

Glacier today is a set of Amazon S3 storage classes — GLACIER_IR, GLACIER and DEEP_ARCHIVE — applied to ordinary objects in ordinary S3 buckets. The older standalone S3 Glacier service stores opaque archives in vaults under its own API and is legacy; new designs should use the S3 storage classes.