SShortSingh.
Back to feed

Key Lessons from Deploying Terraform Enterprise Active-Active on OpenShift

0
·1 views

A developer shared five critical challenges encountered while running Terraform Enterprise (TFE) in active-active mode on OpenShift, deployed via a GitOps pattern using ArgoCD. A major issue was TFE's version incompatibility during rolling updates, caused by the Helm chart's default RollingUpdate strategy; switching to a Recreate deployment strategy resolved the crash-loop failures. Vault's dynamic database role approach proved insufficient for TFE, which requires full database ownership, and was fixed by combining dynamic roles with a static role for the primary application user. TLS certificate errors when connecting to NooBaa S3-compatible storage were resolved by mounting OpenShift's internal CA certificate into the TFE pod. These findings highlight key configuration adjustments needed for a stable TFE active-active deployment in an OpenShift environment.

Read the full story at DEV Community

This is an AI-generated summary. ShortSingh links to the original source for the complete article.

Discussion (0)

Log in to join the discussion and vote.

Log in

Related stories

0
ProgrammingDEV Community ·

Software Engineer Shares Personal Journey From Islam to Christianity

A software engineer originally published a personal essay on April 8, 2026, describing his religious journey from Islam to Christianity, later reposting it on DEV Community. Raised Muslim, he writes that he carried his faith as an inherited identity rather than a consciously examined belief. Over time, he grew uncomfortable with what he describes as performing faith without truly understanding it, which prompted deeper questioning. He acknowledges that fear of being wrong or losing social belonging often prevents people from examining long-held beliefs. The author, who is not a theologian, emphasizes he is sharing a personal experience and does not intend to claim any religion is superior to another.

0
ProgrammingDEV Community ·

Hybrid Encryption Combines Classic and Post-Quantum Crypto for Future-Proof Security

Hybrid encryption addresses a core tension in modern cryptography by pairing battle-tested classical algorithms, such as X25519 and Ed25519, with newer post-quantum standards like ML-KEM-1024 and ML-DSA-87. The approach ensures a system remains secure unless both algorithms are broken simultaneously, making it resilient against both classical and quantum attackers. Key exchange and digital signatures each use an AND-combination model, where both algorithm outputs must succeed for the operation to be valid. An open-source library called Quipu implements this hybrid model for data at rest, operating at NIST Security Level 5 under the CNSA 2.0 framework. However, Quipu's composition of these primitives has not yet undergone an independent cryptographic audit, which experts recommend before deploying it for high-value sensitive data.

0
ProgrammingDEV Community ·

Opinion: Language's Limits Make Artificial Superintelligence Unachievable, Argues Developer

A developer writing on DEV Community argues that language is fundamentally limited as a representation of thought, meaning, and intelligence. The author contends that words are merely symbols that are always smaller than the ideas they attempt to describe, resulting in inevitable gaps in communication. Because current AI systems are largely built on language and text, the author believes they inherit these same limitations and cannot transcend them by simply processing more data. The piece challenges the assumption that scaling up language models will eventually produce superintelligence, arguing that human cognition relies on signals, instinct, memory, and subconscious processes that never translate into words. The author concludes that any machine primarily grounded in language cannot achieve true artificial superintelligence for this reason.

0
ProgrammingDEV Community ·

Engineer Argues LLMs Exploit Developer Knowledge Without Fair Compensation

A software engineer writing on DEV Community contends that AI language models are built on and sustained by human expertise, yet charge users for access rather than compensating contributors. The author argues that every prompt encodes years of professional skill, meaning engineers effectively subsidize these systems while paying per token to use them. The post frames this dynamic as an exploitative arrangement disguised as a productivity service. Originally published in April 2026, the piece is part of a broader personal series the author is reposting to DEV for wider discussion. The author invites community engagement and is available to respond on weekends.