[ci] Migrate microbenchmark, benchmark-worker-startup, and rllib compute configs to new schema

[sai-miduthuri]

Summary

• Migrate 10 compute config files to the new Anyscale SDK schema (cloud_id -> cloud, head_node_type -> head_node, worker_node_types -> worker_nodes, etc.)
• Add anyscale_sdk_2026: true flag to 12 test cluster blocks in release_tests.yaml

Config files migrated

• release/microbenchmark/tpl_64.yaml (AWS, head-only)
• release/microbenchmark/tpl_64_gce.yaml (GCE, head-only)
• release/microbenchmark/experimental/compute_t4_gpu.yaml (AWS, head-only GPU)
• release/microbenchmark/experimental/compute_gpu_2x1_aws.yaml (AWS, head+worker GPU)
• release/microbenchmark/experimental/compute_a100_gpu.yaml (AWS, head-only GPU)
• release/microbenchmark/experimental/compute_l4_gpu.yaml (AWS, head-only GPU)
• release/microbenchmark/experimental/compute_l4_gpu_2x1_aws.yaml (AWS, head+worker GPU)
• release/benchmark-worker-startup/only_head_node_1gpu_64cpu.yaml (AWS, head-only GPU)
• release/benchmark-worker-startup/only_head_node_1gpu_64cpu_gce.yaml (GCE, head-only)
• release/rllib_tests/1gpu_16cpus.yaml (AWS, head-only GPU)

Tests updated with anyscale_sdk_2026: true

• microbenchmark (base + GCE variation)
• compiled_graphs
• compiled_graphs_GPU
• compiled_graphs_GPU_multinode
• compiled_graphs_GPU_cu130
• compiled_graphs_GPU_multinode_cu130
• rdt_single_node_T4_microbenchmark
• rdt_single_node_A100_microbenchmark
• benchmark_worker_startup (base + GCE variation)
• rllib_learning_tests_pong_appo_torch

Test plan

• All 10 config files validated against ComputeConfig.from_yaml()
• CI passes with the new configs

🤖 Generated with Claude Code

[gemini-code-assist]

Code Review

This pull request migrates several release test configuration files to a new schema, involving field renames such as "cloud_id" to "cloud" and "head_node_type" to "head_node", and standardizing resource keys to uppercase. It also adds the "anyscale_sdk_2026" flag to various test definitions. A logical inconsistency was identified in "only_head_node_1gpu_64cpu.yaml" where the resource definition specifies 64 GPUs, contradicting the filename and physical instance capacity.

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