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Graph/assumptive-storage-and-metadata-handling

AntiPattern

S3/Lambda Operational Edge Cases

assumptive-storage-and-metadata-handling

S3 metadata and storage behaviors diverge from developer expectations—object key naming, pagination, lifecycle effects, temp-disk limits, and multipart/columnar reads—causing incomplete listings, unexpected deletions, partial data access, or runtime failures during automation.

Node Details

Public graph metadata

Updated6/29/2026

Connections

30 linked nodes

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bypassing Spark's native S3 file reading and using Boto3 to read files in parallel — This reduced my processing time from 4 hours to 20 minutes. Tension: Spark's native S3 file reading.

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I was able to resolve this by using Cloudwatch EventBridge to monitor S3 CreateObject event and use that as a trigger. Tension: Once I removed the S3 trigger. Outcome: it works perfectly now.

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view an object's S3 Intelligent Tiering access tier through an S3 Inventory report — Configure S3 Inventory. Tension: This can be enabled on a bucket or prefix level and is generated on a daily or weekly frequency. Outcome: download the file from the S3 Inventory output location and parse if locally or query it via Athena.

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Use S3 Metadata tables and query e_tag with Athena or another Iceberg-compatible tool to locate duplicate objects

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Add a policy to the IAM Role that is assigned to the Lambda function — If Alexa is successfully invoking your AWS Lambda function, but the Lambda function is having problems accessing content from Amazon S3. Outcome: The policy should grant the Lambda function permission to access the s3 bucket.

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Then, have this event notification trigger a lambda function — on new file creation or file modification on bucket A. Tension: This isn't possible with s3 sync. Outcome: which copies the file from bucket A to bucket B.

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Have you checked what your csv file sizes are? — By default lambda gives you 512 MB of storage but it can go upto 10 GB now. Tension: there is a possibility that the temp storage is getting exceeded. Outcome: Lambda Ephemeral Storage Update.

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Simply create an endpoint for each of the source database target endpoints — When the DMS Task's Endpoint is S3. Outcome: name the bucket properties based on the source database.

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Use Flink FileSystem and/or flink FileSource.forRecordStreamFormat(...) to read on s3

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To handle S3 EventBridge events, you need to add the `Amazon.Lambda.CloudWatchEvents` NuGet package to the project. — The Lambda function will look like this. Tension: If you are wondering why the package is called `Amazon.Lambda.CloudWatchEvents`, it is because CloudWatch Events is the predecessor of EventBridge. Outcome: Run `dotnet add package Amazon.Lambda.CloudWatchEvents`.

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If your job is simple and can be solved using vanilla python, you should choose that. — AWS Glue ETL job to update data stored in S3 Objects to an existing table in DDB. Tension: There is no official numbers provided by AWS. Outcome: Also consider using packages i.e. Pandas, PyArrow etc. for performance improvement.

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The filesize metadata was a number — in the lambda. Tension: I just hadn't ensured that my metadata values were all strings. Outcome: once I converted it to a string in the lambda and added that value to the metadata all was well.

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Consider using some kind of rate limiter — When downloading locally, it takes effort to generate those 5000 reads. Tension: You are limited to 5000 reads/second down a single s3 partitions. Outcome: to hold back the reads below the threshold.

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Change the S3 event configuration to use a broader object creation event such as “All Object Create Events” (e.g., s3:ObjectCreated:*) so the Lambda triggers for typical PutObject-based uploads.

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you'll need to implement pagination in your API calls — To overcome the issue of 999+ objects limit. Outcome: Create lambda function, which get triggered upon `s3:fileUpload`.

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Create lambda function, which get triggered upon `s3:fileUpload`. — Further you can write status to db and check using query whenever required. Outcome: Further you can write status to db.

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Please review my Lambda function code and help me identify the issue? — I have verified the environment variables, IAM permissions, and the input event JSON. Outcome: I suspect there might be an issue with my Lambda function.

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Make sure you have the region in your s3 location — CREATE EXTERNAL DATA SOURCE s3_ds. Tension: did not have the region in the URL.

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Use AWS DMS. Tension: It solves the schema port issue. Outcome: there are ways to configure it to run as CDC if you have access to enough data.

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Temporarily tweak the replication settings of your S3 bucket — Upload a test file to the source bucket in the active region. Tension: Since we intentionally modified the replication configuration, this action is expected to lead to a replication failure. Outcome: After completing the testing phase, restore the replication configuration to its original state to return to normal replication behavior.

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override the copy method, and use your own marshaller — inherit the AmazonS3Client class. Tension: your operations will succeed, although the tags behavior will not match the one you would expect with S3. Outcome: your operations will succeed, although the tags behavior will not match the one you would expect with S3.

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which principal is deleting your S3 lifecycle rule(s) — CloudTrail management events in the CloudTrail console. Tension: some sort of automation that removes your lifecycle rule. Outcome: Viewing recent CloudTrail management events in the CloudTrail console.

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It should be possible to mount the s3 bucket as ec2 local directory using mountpoint-s3. — directly pointing to s3 bucket is not supported by airflow. Tension: I want to use dags from s3 location. Outcome: point dags_folder to the dags folder under the mounted directory.

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mock/fake/dummy S3 — simulate your desired test scenarios. Outcome: remove S3 from the problem and replace it with something that provides the same contract as S3.

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Trigger an AWS Lambda function whenever objects are created — whenever objects are created. Tension: write some code that either operates on the object immediately or writes the object information to a database. Outcome: it can be accessed quickly in future.

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This type of encryption is free and transparent — Amazon S3 now applies server-side encryption with Amazon S3 managed keys (SSE-S3) as the base level of encryption for every bucket in Amazon S3. Tension: No. It is not allowed to disable encryption. Outcome: This type of encryption is free and transparent, so there's no compelling reason to turn it off anyway.

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Check AWS documentation (2023 version) — for more tips related to lifecycle rules. Outcome: newly created S3 lifecycle rules do apply to both new and preexisting objects.

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Use cron if you need conditional logic (e.g., based on age and other criteria like counts). Otherwise, prefer S3 automation; if you use cron, add monitoring/alerting to detect job failures.

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AWS Step Functions has a built-in pattern to process items in S3 — iterate over all the objects in a chosen bucket (or folder, etc.) that match your description. Tension: This would iterate over all the objects in a chosen bucket (or folder, etc.) that match your description. Outcome: Each object could then be sent to a Lambda function to save its contents to OpenSearch.

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You should use AWS SSM Parameter Store `SecureString`, or AWS Secrets Manager to store these values. — When using Secrets Manager, or when using SSM Parameter Store `SecureString`, the value will be encrypted using AWS KMS. Tension: Your Lambda function will need the relevant IAM permissions to access the secure parameter/secret, as well as decrypt permissions for the KMS key. Outcome: tell SSM or Secrets Manager to use that key for encryption.

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