internal-comms
ANanthropics/skills181k1,119 new stars in the last 7 days
Migrate a legacy AWS Glue development endpoint to a Glue interactive session, following the official AWS migration checklist. Inventories the dev endpoint config, maps it to an equivalent interactive session (runtime role, Glue version, workers, VPC connection, idle timeout), provisions the session, validates by running the developer's Spark/PySpark code, and deletes the dev endpoint after the user confirms. Use when: migrate glue dev endpoint, move off dev endpoints, dev endpoint to interactive sessions, replace glue dev endpoint, glue dev endpoint deprecated, modernize glue dev environment. Do NOT use for: upgrading a Glue ETL job version 0.9/1.0 to 4.0 (use glue-09-10-migration), creating a brand-new interactive session with no source dev endpoint, or migrating dev endpoints to Amazon EMR.
Move a developer off a legacy Glue development endpoint (Glue 0.9/1.0, no console since March 2023, billed continuously) onto a Glue interactive session (Glue 2.0+, sub-minute startup, idle timeout, console support). Follows the official checklist: https://docs.aws.amazon.com/glue/latest/dg/development-migration-checklist.html
The migration is additive and reversible until the final step: the session is created and validated alongside the still-running dev endpoint. The dev endpoint is deleted only after the user confirms the session works.
1.1. Confirm inputs: dev endpoint name, region, AWS CLI profile. MUST NOT proceed without a dev endpoint name.
1.2. Call glue:GetDevEndpoint(EndpointName=<name>). Store as source. Record:
RoleArn, GlueVersion, WorkerType, NumberOfWorkers (or NumberOfNodes),
SubnetId, SecurityGroupIds, Arguments, ExtraPythonLibsS3Path,
ExtraJarsS3Path, PublicAddress/PrivateAddress, Status.
1.3. Route on access method — ask the user how they use the dev endpoint today
(or infer from source). This determines the session interface, per the official
checklist. See the decision table in references/migration-mapping.md:
.ipynb)aws-glue-sessions package1.4. Route on code compatibility (this is the hard gate): interactive sessions run Glue 2.0+ only — they cannot run 0.9/1.0. If the dev endpoint's scripts depend on 0.9/1.0-specific behavior (HDFS, YARN configs, Spark 2.x semantics, Python 2 syntax), the code MUST be upgraded to Glue 3.0+ first.
glue-09-10-migration skill (its breaking-change catalogue covers Spark 2.x→3.x,
Python 2→3, Scala, Log4j, Parquet timestamps) BEFORE provisioning the session.Interactive sessions need two principals (the #1 setup failure). See
references/migration-mapping.md for exact policies.
CreateSession. Reuse the dev endpoint's RoleArn —
it already has the right Glue job permissions and trusts glue.amazonaws.com.AWSGlueConsoleFullAccess) AND
iam:PassRole on the runtime role. Verify before creating the session.Build session config by mapping source fields (full table in the reference):
| Dev endpoint | Session setting |
|---|---|
RoleArn | --role (runtime role) |
GlueVersion 0.9/1.0 | --glue-version 3.0 (or 4.0/5.0); never 0.9/1.0 |
WorkerType / NumberOfWorkers | --worker-type / --number-of-workers (default 5) |
SubnetId + SecurityGroupIds | a Glue connection referenced via %connections / --connections |
ExtraPythonLibsS3Path | %additional_python_modules |
ExtraJarsS3Path | %extra_jars |
--enable-glue-datacatalog arg | session default arg / %%configure |
| (dev endpoints never time out) | --idle-timeout <min> — always set this |
3.1. Default: --glue-version 4.0, same WorkerType/NumberOfWorkers as the
dev endpoint, --idle-timeout 30, Python 3. Override on request ("use Glue 3.0",
"use 10 workers", "idle timeout 60").
3.2. Create via the user's chosen interface:
%iam_role, %glue_version, %worker_type, %number_of_workers,
%idle_timeout, %connections — then run a cell to start the session.glue:CreateSession with
--id, --role, --command Name=glueetl,PythonVersion=3, --glue-version,
--worker-type, --number-of-workers, --idle-timeout. Poll glue:GetSession
until Status=READY (typically under 1 minute).4.1. Run the developer's actual Spark/PySpark code in the new session and compare output to the dev endpoint.
.ipynb cells; confirm no errors and matching
results.glue:RunStatement(SessionId, Code), poll
glue:GetStatement until Statement.State=AVAILABLE, then read the result from
Statement.Output.Data.TextPlain (the exact JSON paths — do not guess). A
Statement.Output.Status=error means the code failed — capture
Statement.Output.ErrorName/ErrorValue.4.2. PASS criterion: the session produces functionally equivalent output. Spark version (2.4.x → 3.3.x+) and Python version (3.6 → 3.10) WILL differ; that is expected and not a failure. On PASS → Step 5.
4.3. On failure, classify the error before doing anything else:
CODE_COMPATIBILITY — a Glue 0.9/1.0 breaking change surfacing on Spark 3.x /
Python 3.10. Signals: SyntaxError, ImportError/ModuleNotFoundError,
No FileSystem for scheme: hdfs, untyped Scala UDF, Log4j 1.x classes, Parquet
timestamp/rebase errors, Scala 2.11 binary incompatibility, AWS SDK 1.11 method
not found. Fix path: use the glue-09-10-migration skill's breaking-change
catalogue to diagnose and patch the code. Validate the patched code by
re-running it in THIS interactive session via glue:RunStatement — do NOT create
or run a Glue job for validation (that is glue-09-10-migration's native
mechanism; here the session is the validation surface). Then re-run 4.1.
MIGRATION_CONFIG_GAP — the code is fine but the session is missing something
the dev endpoint provided. Signals: cannot reach a VPC data store (no Glue
connection), ModuleNotFoundError for a lib that was in ExtraPythonLibsS3Path,
ClassNotFoundException for a jar that was in ExtraJarsS3Path, catalog tables
not found (--enable-glue-datacatalog not carried over). Fix path: patch the
session config (add %connections/--connections, %additional_python_modules,
%extra_jars, or the catalog arg) per the mapping in Step 3, recreate the session,
and re-run 4.1.
TRANSIENT — provisioning/throttling/internal errors with no user-code traceback. Fix path: retry 4.1 once.
4.4. Attempt budget (mirrors glue-09-10-migration): MAX_FIX_ATTEMPTS = 5.
Each fix-and-rerun consumes one attempt. After each failure, compute a fingerprint
(error_name + ":" + failing_symbol); if a fingerprint repeats (the same failure
recurred after its fix), go to the Exit path immediately — do not burn the rest of
the budget on a fix that is not converging. If the error matches no class in 4.3, go
to the Exit path. On reaching 5 attempts without a PASS, go to the Exit path.
4.5. Exit path (validation cannot be made to pass): MUST NOT proceed to Step 5 and
MUST NOT delete the dev endpoint — it is the rollback. Keep the dev endpoint running.
Stop the session (glue:StopSession) to avoid cost, but leave it for debugging.
Report classification, the error, what was tried, and manual next steps:
MIGRATION RESULT: VALIDATION FAILED — dev endpoint RETAINED
Dev endpoint: <name> (Glue <ver>) -> KEPT (rollback intact)
Interactive session: <id> -> STOPPED (kept for debugging)
Halt reason: <BUDGET_EXHAUSTED|CYCLE_DETECTED|UNCLASSIFIED>
Failure class: <CODE_COMPATIBILITY|MIGRATION_CONFIG_GAP|TRANSIENT|UNCLASSIFIED>
Error: <ErrorName>: <ErrorValue>
Fixes attempted: [list]
Manual next steps: [list]
5.1. Present the validation result, then explicitly ask the user to confirm deletion
of the dev endpoint — it is the rollback path. Ask a direct yes/no question naming
the endpoint, for example: "Validation passed. Delete dev endpoint '<name>' in <region> now? Its definition will be backed up to S3 first. (yes/no)" MUST wait for an
affirmative reply. Treat anything other than a clear yes (no answer, "later", "keep
it", silence) as NO: skip deletion, leave the dev endpoint running, and tell the user
it was kept and how to delete it themselves later. MUST NOT delete on assumption or to
"save cost" without this explicit yes.
5.2. Back up the dev endpoint definition before deleting (MUST NOT skip). A
deleted dev endpoint cannot be recovered, so persist its full config first. Write the
source definition captured in Step 1.2 (the raw glue:GetDevEndpoint response) as
JSON to S3 — default s3://<a bucket the runtime role can write>/glue-devendpoint-backups/<name>-<region>.json;
ask the user for the bucket if none is evident. This is the rebuild record: it captures
RoleArn, GlueVersion, WorkerType/NumberOfWorkers, SubnetId,
SecurityGroupIds, Arguments, ExtraPythonLibsS3Path, ExtraJarsS3Path, and
PublicKeys, so the endpoint can be recreated with glue:CreateDevEndpoint if the
migration must be rolled back. Confirm the s3:PutObject succeeded before proceeding.
5.3. On confirmation and a confirmed backup: glue:DeleteDevEndpoint(EndpointName=<name>).
Remove any endpoint-specific scaffolding the migration added (registered SSH public
keys, temporary Elastic IPs).
5.4. Output the result:
MIGRATION RESULT: SUCCESS
Dev endpoint: <name> (Glue <ver>) -> DELETED
Definition backup: s3://<bucket>/glue-devendpoint-backups/<name>-<region>.json
Interactive session: <id> (Glue 4.0)
Access method: <notebook|IDE|REPL|docker>
Code upgrade: <none | via glue-09-10-migration>
Validation: PASSED (output matched)
Idle timeout: <n> min
glue-09-10-migration.iam:PassRole on the client principal is the most
common CreateSession/AccessDenied failure. The runtime role alone is not enough.--idle-timeout. Dev endpoints never timed out and billed 24/7. A
session with no idle timeout reintroduces that cost. Default 30 min.SubnetId + SecurityGroupIds become a named
Glue connection referenced by %connections. There is no raw-subnet session arg.%additional_python_modules supports PyPI and S3 wheels.glue:CreateDevEndpoint. MUST NOT skip, even when the user says "just delete it."DynamicFrame.fromDF emits a benign UserWarning on Spark 3.x ("DataFrame
constructor is internal"). It is not an error; output is unaffected.| Error | Cause | Fix |
|---|---|---|
AccessDeniedException on CreateSession | Client principal lacks session API perms or iam:PassRole | Attach AWSGlueConsoleFullAccess (or session API perms) AND iam:PassRole on the runtime role to the client principal |
CreateSession fails on runtime role | Runtime role missing glue.amazonaws.com trust or Glue permissions | Reuse the dev endpoint's RoleArn, or attach AWSGlueServiceRole with the Glue trust policy |
Statement State=ERROR with IllegalArgumentException/SyntaxError at start | Code has Glue 0.9/1.0 (Python 2 / Spark 2.x) constructs | Upgrade the code to Glue 3.0+ first via glue-09-10-migration, then re-run |
No FileSystem for scheme: hdfs | Script uses HDFS (not present in Glue 3.0+) | Repoint to S3; covered by glue-09-10-migration HDFS_PATH handling |
| Session works but cannot reach a VPC data store | No Glue connection attached | Create a Glue connection for the subnet/SGs and pass it via %connections / --connections |
Session already exists on CreateSession | An earlier session with the same --id is still alive | Pick a new --id, or glue:DeleteSession the stale one first |
references/migration-mapping.md — full config mapping, access-method decision
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