Archived *** redesign required ***

This repository has been archived due to its poor design:

• Code engine jobs are limited to 100 jobs / 10 minutes. Flow logs can easily surpass this. Job frequency documentation:
  • Subscriptions for jobs and job run limitations
  • Running jobs in parallel
• IBM Log Analysis has been deprecated and replaced with IBM Cloud Logs.

Recommendation to update this example, choose one:

• Integrate the COS buckets with Analytics Engine. Similar to this blog post only using analytics engine instead of SQL Query/.
• Use code engine application instead of a job with IBM Cloud Logs.

Analyze VPC Flow Logs

This repository is the companion to the blog post Use IBM Code Engine to push IBM VPC Flow Logs to IBM Log Analysis for analysis

Flow logs for VPC persists a digest of network traffic in a Virtual Private Clouds (VPC) in a Cloud Object Storage (COS) bucket.

Code Engine can be extended by integrating with Cloud Object Storage (COS). The COS trigger type lets you run custom code logic when a new object is stored, updated, or deleted from a designated bucket in COS.

This project shows how use a Code Engine notification to start the excecution of a Code Engine job which will read a flow log COS object and write it to IBM log analysis.

1. The Flow logs for VPC are written to a COS bucket.
2. Cloud Object Storage works with Code Engine to execute the job.
3. Job reads the COS bucket object using an apikey for authorization
4. Job writes the log entries

Create demo VPC, COS bucket and logdna

If you do not have a vpc use the scripts below to create a vpc, COS bucket, logging service instance. The script also creates a code_engine_config.sh file.

# create a demo.env file with some terraform variables tht suite your taste
cp template.demo.env demo.env
edit demo.env
source demo.env

# verify prerequisites
000-demo-prerequisites.sh

# execute terraform and create a code_engine_config.sh file
100-demo-vpc-and-flowlog-bucket-create.sh

# take a look at the code_engine_config.sh file and note that it contains a logdna ingestion key secret - keep the file safe
cat code_engine_config.sh

Configure your existing VPC

If you already have a vpc you have a couple of options

Option 1 - Add to my existing VPC via terraform configuration

If your vpc was created with terraform add the terraform module as described in README.md

Option 2 - Create your own COS bucket and Logging instance

make make sure that it has been configured with flowlogs and you know the details of the bucket containing the flowlogs, and a Logging service instance and ingestion key.

To find the bucket navigate to the Resources view and in the Storage section open your Cloud Object Storage instance. Open the Bucket and then open the Configuration and find the Direct endpoint and the Bucket instance CRN

To find the LOGDNA constants visit Observability Logging and click on your logging instance. The region is a string like "us-south". Click Actions, click view Ingestion key

Create the code_engine_config.sh file with your fingers:

# read the comments in the file and configure variables to match your COS bucket and logdna configuration
cp template.code_engine_config.sh code_engine_config.sh
edit code_engine_config.sh

The file code_engine_more_config.sh has a few more configuration variables that typically do not require edits. Open the file in an editor and verify.

Create code engine related resources

The script 150-ce-prerequisites.sh will verify that some of the configuration has been successfully completed (it could use some more work)

The script 200-create-ce-project-logging-and-keys.sh will create resources as shown in the diagram above:

• IAM service ID allowing access to COS and associated apikey
• code engine project
• code engine config map passed as environment variables to the job
• code engine secrets for apikey and logdna ingestion key passed as environment variables to the job
• service authorization allowing flow logs to write to a COS bucket.
• code engine job
• code engine subscription from the COS bucket to the job

All this was configured based on the contents of the two files:

• code_engine_config.sh
• code_engine_more_config.sh

If you want to walk more slowly through the source code or make your own Docker image go to Development below. Otherwise continue:

ibmcloud login
./150-ce-prerequsites.sh
./200-create-ce-project-logging-and-keys.sh

Observe the logs

In the ibm cloud console visit Observability Logging and click on your logging instance. Then click on Open Dashboard to open the actual logs. You should start to see VPC flow logs in about 10 minutes.

If you do not see the logs check out Troubleshooting below

Clean up

To destroy the code engine project, the logging instance, service id and authorization:

./800-cleanup-code-engine.sh

If you created the demo VPC, COS instance and bucket:

./900-cleanup-demo.sh

Development

This section is for those that want to dig deeper into the source code or debug

Debug the python program on your desktop

The python scripts in the job/ directory require some configuration variables. The scripts below will create the code engine project but not the code engine job. The code engine configmap and secrets will also be created and are needed to test the python code.

./150-ce-prerequsites.sh
./200-create-ce-project-logging-and-keys.sh basics; # project, configmap and secrets
./300-python-debug-config.sh; # make python.ini with configuration including secrets for running locally

Set up your python 3.9 environment. I use a virtual python environment on my laptop.

$ python --version
Python 3.9.6

Python source code is in the job/ directory

cd job
pip install --no-cache-dir -r requirements.txt

The python script ./test_flowlog_to_logdna.py can be executed to find a key in the cos bucket and send it to logdna. You can make some changes to this file to test different scenarios.

Create a docker image

Create a docker image on your desktop and push it to docker hub.

Work in the job/ directory:

cd job

The scripts use the configuration file:

grep DOCKER  ../code_engine_more_config.sh
export DOCKER_IMAGE=icr.io/solution-tutorials/sample-flowlog-logdna:latest

You must use your own docker repository in docker hub. Change the environment variable in the file and export it into your environment:

# change DOCKER_IMAGE=YourRepository/flowlog:1.0
edit ../code_engine_more_config.sh

# actually export it into your current shell environment to allow the Makefile to work
grep DOCKER  ../code_engine_more_config.sh
export DOCKER_IMAGE=YourRepository/flowlog:1.0
# now export DOCKER_IMAGE into your shell environment:
export DOCKER_IMAGE=YourRepository/flowlog:1.0

A makefile will build it for you, if you do not have make available type the commands in the Makefile with your fingers.

make docker-build
make docker-push

Deploy using your own docker image. The script is smart enough to update the resources that were created earlier if they exist:

./150-ce-prerequsites.sh
./200-create-ce-project-logging-and-keys.sh

Log existing flow logs

This section explains how to send the objects previously created to logdna. The steps above log the new flow logs as they are written, but you may have a bucket full of old flow logs that you want to analize.

Create the basic code engine project and environment then create a job:

./150-ce-prerequsites
./200-create-ce-project-logging-and-keys.sh basic
./200-create-ce-project-logging-and-keys.sh job

Check out the job in the IBM cloud console in the Code Engine Projects

• Click on your project to open it up. Notice the Secrets and Configmaps tab and the Jobs tab
• Click on the Jobs tab
• Click on your job if you submit the job all of the VPC flow log objects in the bucket will be written to the Logging instance. This has been tested with a few thousand, but you could have more if you have been accumulating them for a few days.

Before creating the job it can be helpful to deploy a platform logging instance in the same region as the code engine job.

Subscribe to COS bucket

After completing the previous step to capture the existing flow logs turn on subscriptions to get the new ones.

The subscription will call the job each time flowlog puts an object into the bucket:

./200-create-ce-project-logging-and-keys.sh job subscription

Troubleshooting

To troubleshoot problems start in the IBM cloud console in the Code Engine Projects

• Click on your project to open it up. Notice the Secrets and Configmaps tab and the Jobs tab
• Click on the Jobs tab
• Click on your job
• You should see some jobs in the Job runs tab. The subscription is starting a job each time an object file is put into the bucket
• In the logs check out the table:
  • Configmap reference - click on the Configmap link and look at the environment variables that will be set in the job run
  • Secret reference - click on the Secret link and verify
    • LOGDNA_INGESTION_KEY - Open the Logging instance, click Actions, click view Ingestion key, verify the Ingestion Keys match.
    • Verify the LOGDNA_REGION matches the region of the logging instance
    • APIKEY - In a terminal window using the APIKEY secret and variables from the Configmap verify that the APIKEY has access to the bucket and objects:
      • ibmcloud login --apikey APIKEY
      • ibmcloud cos config crn --crn COS_CRN
      • ibmcloud cos objects --bucket COS_BUCKET
      • ibmcloud cos get-object --bucket COS_BUCKET --key key_from_previous_command
      • do not forget to restore your normal login!
  • CE_DATA. Verify the keys "bucket" and "key" are visible.
• click on the Launch logging button and the IBM logging environment will be opened and at the bottom you will notice it is filtered specifically for the log entries printed by the python program. This may be enough to pin point the problem.
• You can get more logs by enabling LOG/DEBUG. Back in your Code Engine Project click the Secrets and Configmaps tab, click on your configmap, click Add key-value pair and add LOG/DEBUG for the Key/Value and click Save.
• The next job will have more logging info
• You should be able to track back to the python program in the job/ folder for problems. You can run the python program on your laptop using the instructions above.
• You can add more logging to the python files test it locally and then follow the instructions above to make a docker image. After pushing the docker image execute ./400-job-create.sh