boto3-refresh-session has received a lot of positive attention and adoption, but it also has detractors. In fact, it has been outright dismissed by a minority of developers online; however, those detractors do not seem understand what set of problems boto3-refresh-session solves or who it is for.

“Just create profiles – it works for every single credential type and will refresh automatically. I don’t know why you would create a library for this when all SDKs work the same with profile configurations.”

This is a very common misunderstanding. While profiles cover many cases, they don’t solve every scenario Python developers encounter.

It is unclear if the origins of those spurious criticisms are rooted in basic misunderstanding or cursory trolling. Either way, I worry teams and individuals who would actually benefit from boto3-refresh-session will occasionally be deterred from evaluating it.

I am therefore compelled to clarify who exactly this package is for and exactly what problems it does and does not solve.

Arguably, it is not my responsibility to edify anyone about credential_process, etc; however, as the founder and core maintainer of boto3-refresh-session, it is my obligation to ensure the community understands, to the best of my ability, what this tool is and is not.

Some examples of what already auto-refreshes (when used correctly):

The following bulletpoints are not an exhaustive list.¹

• EC2 instance roles (IMDS): Botocore’s EC2 provider fetches / rotates credentials from the instance metadata service automatically. No manual refresh needed in long-running apps if you let the default provider chain run.

• ECS / Fargate task roles (task metadata endpoint): Botocore’s ECS provider pulls / renews task role creds via the container credentials endpoint automatically. ²

• credential_process (in ~/.aws/config): if the external process returns JSON with an Expiration, botocore treats it as refreshable and will re-invoke before expiry. (If you hardcode creds or the process omits expiration, you lose true refresh semantics.)

• AssumeRole via profile (role_arn + source_profile): using a named profile (not hardcoded env vars) lets botocore renew the STS session behind the scenes.

• Web identity (IRSA on EKS): the SDK exchanges the projected token and refreshes as needed.

Some examples of when that isn’t true (common foot-guns for Python devs):

The following bulletpoints are also not an exhaustive list.¹

• You bypass the provider chain. Example: exporting AWS_ACCESS_KEY_ID | SECRET | SESSION_TOKEN from a one-off aws sts assume-role and then launching a long process. Or sidestepping the standard credential provider in ECS. Those tokens expire and will not auto-refresh. That is where RefreshableSession(method="custom") becomes helpful.

• You pass explicit credentials to boto3.Session(...). Providing keys directly (or reading them once from a file) fixes the credentials for the life of the process — no refresh.

• Profiles without expiration semantics. If your credential_process doesn’t emit Expiration, the SDK can’t plan a refresh (it treats them as static/opaque).

• Network / metadata blocked. Enterprises that block IMDSv2 or ECS task endpoints (or container lacks the env wiring) break auto-refresh even on EC2 / ECS (as mentioned above).

• SSO & very long runtimes. SSO profiles refresh while the device token is valid, but headless, weeks-long daemons can still hit interactive renewal walls.³

• IoT credentials (X.509). The AWS IoT credentials provider (mTLS to the IoT endpoint, role alias, then STS creds) is not a built-in botocore provider. Out of the box, the SDK won’t auto-renew those for you.

• credential_process binaries can be brittle, i.e. difficult to maintain and distribute.

Who boto3-refresh-session is for (and not)

boto3-refresh-session is for Python developers who need a robust, Python-native way to handle expiring credentials — whether because they can’t rely on credential_process, they’re embedding boto3 in long-running daemons, or they’re working with IoT / X.509 flows that the standard provider chain doesn’t support.

boto3-refresh-session is not for people who use the standard ECS / EC2 credential provider, depend upon credential_process without friction, or are not aware of the limitations and edge cases associated with profiles, AWS credential providers, etc.

Reflections

boto3-refresh-session isn’t the easiest package to explain; it is a niche backend Python package. It doesn’t lend itself to a pithy, one-line slogan, which can make the README challenging to keep concise. In some ways, boto3-refresh-session is less about who it’s for than not. Which is odd.

What reassures me is that the engineers and teams who found this project and adopted it tend to be highly competent, and so far the lack of open issues or pull requests suggests the library is stable and working as intended.

Still, I want to make this tool accessible to the very developers I originally had in mind when I published this project — namely, engineers and data scientists who struggle with expiring credentials in long-lived processes and don’t want to hand-roll refresh logic (or can’t - for whatever reason). My hope is this post clarifies common misconceptions about what this project is and is not, and why it exists.

If you’re a Python developer working with long-running workloads, IoT / X.509 flows, or any environment where the standard provider chain falls short, boto3-refresh-session exists so you can stop worrying about credentials and focus on your application.

If you have questions, reach out via GitHub or any of the usual channels.