Oracle engineers caused five days software outage at U.S. hospitals

Why organizations still buy Oracle / Cerner

• Several comments argue Oracle wins through aggressive enterprise sales: courting executives/CTOs with “we’ll handle everything” pitches, not developer preference.
• Others note in this case “Oracle wasn’t bought, Cerner was” and that Cerner’s core products historically sat on Oracle backends.
• Oracle is seen as offering a full-stack menu (DB, ERP, identity, CRM, cloud, etc.) that appeals to large bureaucracies wanting one vendor and “one throat to choke.”
• Some mention educational seeding: universities teaching Java/Oracle stacks create a pipeline of Oracle-literate juniors.

Legacy lock‑in, mainframes, and COBOL

• Many see Oracle use as legacy lock‑in: systems built decades ago when alternatives were weaker, now too risky/expensive to replace.
• Comparisons to COBOL/mainframes: systems run for 40–60 years, deeply embedded in business processes; migration is huge and rarely justified if the old system “still works.”
• Discussion on COBOL careers: some say it’s a high-pay, long-term niche; others call it “zombieware” that young devs avoid.
• A few suggest AI-assisted codebase translation as an unexplored opportunity, but others note the complexity and risk.

Technical views on Oracle vs Postgres/SQL Server

• Strong split: many insist Postgres is better for 99% of use cases; others say if money is no object, OracleDB still wins for extreme scale and fine-grained control.
• Examples cited: Oracle’s partitioned global unique indexes, ability to pin/prioritize execution plans, Exadata storage-level optimizations.
• Postgres’s refusal to fully honor query hints is highlighted as a pain point in some mission-critical scenarios.
• Some note OracleDB is technically impressive but surrounded by awful licensing, audits, tooling, and operational complexity.
• Others argue Oracle quality is generally low across its vast product line, even if the core database engine is strong.

Cause of the outage: human error vs process failure

• The reported root cause (“engineers deleted critical storage”) leads many to blame poor change management rather than individual engineers.
• Several describe what good process should look like in healthcare: strict procedures, staged disablement, read‑only aging, delayed physical deletion, clear rollback and recovery plans.
• The multi-day recovery time is read as evidence that procedures, safeguards, and tested backups were inadequate.

Culture, blame, and management pressure

• Debate around whether such failures stem from unrealistic deadlines and executive pressure vs plain incompetence or bad ops hygiene.
• Some argue it’s a pattern: decisions and budgets arrive late, but delivery dates don’t move, forcing compressed, risky work.
• Others push back on reflexively blaming management, emphasizing that individuals and organizations both share responsibility.

LLMs, “vibe coding,” and reliability

• Thread digresses into AI-assisted “vibe coding”: rapid progress initially but poor architecture, weak understanding, and fragile prototypes.
• Experienced developers report that heavy LLM reliance can degrade learning and insight; LLMs are seen as powerful search/idea tools, not mentors or safety nets.
• Concern that novices using LLMs may ship systems they don’t understand deeply enough to debug safely in critical environments.

Healthcare / EHR specifics and Cerner design

• Cerner’s architecture is criticized: shared “multitenant” database setups for multiple hospitals and high access privileges (e.g., widespread SSH and production DB write access).
• Multiple EHRs (Cerner, Epic, others) are described as dreadful from clinician and operational perspectives, even when technically “up.”
• Some note regional regulatory constraints (e.g., strict privacy rules) making generic EHR products hard to adapt.
• Skepticism that Oracle’s future AI-based EHR will prioritize real quality over marketing.