Where database blog posts get flame-broiled to perfection
Alright team, gather 'round. Marketing just forwarded me the latest "thought leadership" piece from one of our... potential database partners. They’ve spent over a thousand words celebrating a “feature” that amounts to rewarding bad programming. Let's dissect this masterpiece of corporate fan-fiction before they try to send us an invoice for the privilege of reading it.
First, they’ve managed to brand “not doing work when nothing changes” as a revolutionary optimization. The central premise here is that our applications are so inefficient—mindlessly updating fields with the exact same data—that we need a database smart enough to clean up the mess. This isn't a feature; it's an expensive crutch for sloppy code. They’re selling us a helmet by arguing we should be running into walls more often. Instead of fixing the leaky faucet in the application layer, they want to sell us a billion-dollar, diamond-encrusted bucket to put underneath it.
Second, let’s talk Total Cost of Ownership. The author needed a Docker container, a log parser, and a deep understanding of write component verbosity just to prove this "benefit." What does that tell me? It tells me that when this system inevitably breaks, we're not calling our in-house team. We're calling a consultant who bills at $400/hour to decipher JSON logs. Let’s do some quick math: One senior engineer's salary to build around these "quirks" ($180k) + one specialized consultant on retainer for when it goes sideways ($100k) + "enterprise-grade" licensing that charges per read, even the useless ones ($250k). Suddenly, this "free optimization" is costing us half a million dollars a year just to avoid writing a proper if statement in the application code.
Third, the comparison to PostgreSQL is a masterclass in spin. They present SQL's behavior—acquiring locks, firing triggers, and creating an audit trail—as a flaw.
In PostgreSQL, an UPDATE statement indicates an intention to perform an operation, and the database executes it even if the stored value remains unchanged. Yes, exactly! That’s called a transaction log. That's called compliance. That’s called knowing what the hell happened. They’re framing predictable, auditable behavior as a burdensome "intention" while positioning their black box as a more enlightened "state." Oh, I see. It's not a bug, it's a philosophical divergence on the nature of persistence. Tell that to the auditors when we can't prove a user attempted to change a record.
Finally, this entire article is the vendor lock-in two-step. They highlight a niche, esoteric behavior that differs from the industry standard. Then, they encourage you to build your entire application architecture around it, praising "idempotent, retry-friendly patterns" that rely on this specific implementation. A few years down the line, when their pricing model "evolves" to charge us based on CPU cycles spent comparing documents to see if they're identical, we're trapped. Migrating off would require a complete logic rewrite. They sell you a unique key, then change the lock every year.
Honestly, sometimes I feel like we're not buying databases anymore; we're funding PhD theses on problems no one actually has. It’s a solution in search of a six-figure support contract. Now, if you'll excuse me, I need to go approve a PO for a new coffee machine. At least I know what that does.
Oh, what a fantastic read. I just love the boundless optimism. It's so refreshing to see someone ask, "Why change something that just works?" with the unstated, yet screamingly obvious answer: for the thrill of a 72-hour production outage!
Truly, it's inspiring. The argument that Redis's greatest strength—that it just works—is also its "potential challenge" is the kind of galaxy-brain take I've come to expect from thought leaders who haven't had to restore a corrupted key space from a six-hour-old backup at 3:00 AM on a Sunday. My eye is twitching just thinking about it.
I'm especially excited about the prospect of another "simple" migration. My therapist and I have been making real progress working through the memories of the last few:
It's always the same beautiful story. It starts with a whitepaper full of promises, moves to a Slack channel full of excitement, and ends in a war room full of cold pizza and broken dreams. I cherish the moment in every migration when a project manager confidently states:
"The migration script is 98% done, it just needs some light testing."
That phrase is my Vietnam. It's the sound of my weekend evaporating. It’s the harbinger of cryptic error messages that don't exist on Stack Overflow.
So yes, let's absolutely replace the one component in our stack that doesn't regularly wake me up with a heart attack. Let's introduce a new, exciting system with its own special, innovative failure modes. I'm tired of the same old Redis outages. I want new ones. I want to debug distributed consensus issues, not simple connection pool exhaustion. I want my problems to be as next-gen as our tech stack.
So thank you for this article. You've given me so much to look forward to. I'm already mentally preparing the post-mortem document and drafting the apology email to our customers.
Anyway, my PagerDuty app is freshly updated. Can't wait for the "go-live." It's going to be transformative.
Alright, let's pull on the latex gloves and perform a public autopsy on this... aspirational document. "Building the foundation of trust in government digital strategies," you say? That sounds less like a strategy and more like the first line of a data breach notification. You’ve built a foundation, alright—a foundation of attack vectors on the bedrock of misplaced optimism.
Let's break down this architectural marvel of naivete, shall we?
Your so-called "foundation of trust" is what I call a "foundational flaw." In a Zero Trust world, "trust" is a four-letter word you scream after you've been breached. You’re not building a foundation; you’re digging a single point of failure. The moment one of your "trusted" microservices gets popped—and it will—your entire glorious house of cards comes tumbling down. This isn't a foundation; it's a welcome mat for lateral movement.
I see you boasting about "seamless citizen services." What I hear is seamlessly siphoning sensitive data. Every API endpoint you expose to "simplify" a process is another gaping maw for unsanitized inputs. I can already picture the SQL injection queries. "Seamless integration" is just marketing-speak for "we chained a bunch of containers together with API keys we hardcoded on a public GitHub repo."
It’s so user-friendly, the script kiddies won't even need to read the documentation to exfiltrate your entire user database.
You're proud of your "agile and adaptive" framework. A security auditor hears "undocumented, un-audited, and pushed to production on a Friday." Your "adaptability" is a feature for attackers, not for you. Every time your devs pivot without a full security review, they're creating a new, delightfully undiscovered vulnerability. This isn't agile development; it's a perpetual motion machine for generating CVEs.
And the compliance angle… oh, the glorious compliance dumpster fire. You think this will pass a SOC 2 audit? Bless your heart. Your auditors will take one look at your logging—assuming you have any—and start laughing. The lack of immutable audit trails, the cavalier way you're handling PII, the "trust-based" architecture... you're not just going to fail your audit; you're going to become a cautionary case study in security textbooks.
Look, it's a cute little PowerPoint slide of an idea. Really. Keep at it. Now, go back to the drawing board and come back when you understand that the only thing you should trust is that every single line of your code will be used against you in a court of law.
Alright team, huddle up. Another vendor success story just hit the wire. This one's about how a bank "transformed" itself with Elastic. Let's pour one out for the ops team over there, because I've read this story a hundred times before, just with a different logo on the cover. I can already tell you how this really went down.
First, we have the claim of a "seamless migration" to this new, unified platform. Seamless. I love that word. It usually means they ran the new system in parallel with the old one for six months, manually cross-referencing everything in a panic because neither system showed the same results. The real "transformation" happens when the old monitoring system is finally shut down, and everyone realizes the new one was never configured to watch the legacy batch job that processes all end-of-day transactions. I can't wait for the frantic call during the next market close, wondering why nothing is moving.
Then there’s the gospel of "a single pane of glass," the holy grail of observability. It's a beautiful idea, like a unicorn that also files your expense reports. In reality, that "single pane" is a 27-tab Chrome window open on a 4K monitor, and the one dashboard you desperately need is the one that's been throwing 503 errors since the last "minor" point-release upgrade. You'll have perfect visibility into the login service while the core banking ledger is silently corrupting itself in the background.
My personal favorite is the understated complexity. The blog post makes it sound like you just point Elastic at your infrastructure and it magically starts finding threats and performance bottlenecks. They conveniently forget to mention that your "observability stack" now has more moving parts than the application it's supposed to be monitoring. It's become a mission-critical service that requires its own on-call rotation. I give it three months before they have an outage of the monitoring system, and the post-mortem reads, "We were blind because the thing that lets us see was broken."
Let’s talk about those "proactive security insights." This translates to the security team buying a new toy and aiming it squarely at my team's production environment. For the first two weeks, my inbox will be flooded with thousands of P1 alerts because a cron job that's been running every hour for five years is now considered a "potential lateral movement attack vector." We'll spend more time tuning the false positives out of the security tool than we do deploying actual code.
So here’s my prediction: at 2:47 AM on the first day of a three-day holiday weekend, the entire Elastic cluster will go into a rolling restart loop. The cause will be something beautifully mundane, like an expired internal TLS certificate nobody knew about. The on-call engineer will find that all the runbooks are out of date, and the "unified" logs detailing the problem are, of course, trapped inside the dead cluster itself. The vendor's support line will blame it on a "misconfigured network ACL."
I'll save a spot on my laptop for the Elastic sticker. It’ll look great right next to my ones from CoreOS, RethinkDB, and all the other silver bullets that were supposed to make my pager stop going off.
Anyway, I have to go provision a bigger disk for the log shippers. Turns out "observability" generates a lot of data. Who knew?
Well, isn't this just a delightfully detailed dissertation on how to turn a perfectly functional database into a high-maintenance, money-devouring monster. I must applaud the author's commitment to exploring solutions that are, and I quote, "not feasible in a managed service environment." That’s exactly the kind of outside-the-box thinking that keeps CFOs like me awake at night, clutching their balance sheets.
It’s truly inspiring to see someone so casually suggest we should just “recompile PostgreSQL.” You say it with the same breezy confidence as someone suggesting we change the office coffee filter. It’s so simple! Just a quick docker build and a few flags. I’m sure our DevOps team, which is already stretched thinner than a budget proposal in Q4, would be thrilled to take on the care and feeding of a custom-built, artisanal database. This "lab setting" you speak of sounds suspiciously like what I call an "un-budgeted and unsupported liability."
Let’s do some quick, back-of-the-napkin math on the “true” cost of this brilliant little maneuver. You know, for fun.
So, this "free" open-source tweak to save a few buffer hits will only cost us around $116,000 up front. A negligible investment, I’m sure. And the beautiful part is the vendor lock-in! We’re not locked into a vendor; we’re locked into the two people in the company who know how this cursed thing works. Brilliant!
And for what? What’s the ROI on this six-figure science project?
Buffers: shared hit=4
...unlike the six buffer hits required in the database with an 8 KB block size.
My goodness, we saved two whole buffer hits! The performance gains must be staggering. We've shaved a whole 0.1 milliseconds off a query. At this rate, we’ll make back our initial $116,000 investment in, let me see... about 4,000 years. This is a fantastically fanciful fiscal framework.
But the masterstroke is the conclusion. After walking us through a perilous and pricey path of self-managed madness, the article pivots to reveal that another database, MongoDB, just does this out of the box. It's a classic bait-and-switch dressed up in technical jargon. You've painstakingly detailed how to build a car engine out of spare parts, only to end with, "Or, you could just buy a Ferrari."
Thank you for this profoundly particular post. It’s been an illuminating look into the world of solutions that generate more problems, costs that hide in plain sight, and performance gains that are statistically indistinguishable from a rounding error.
I’ll be sure to file this under "Things That Sound Free But Aren’t." Rest assured, I won't be reading this blog again, but I wish you the best of luck with your next spectacularly expensive suggestion.
Cheerio
Ah, yes, another missive from the front lines of industry. "JVM essentials for Elasticsearch." How utterly... practical. It's a title that conjures images of earnest young men in hoodies frantically tweaking heap sizes, a task they seem to regard with the same gravity with which we once approached the P vs. NP problem. One must admire their focus on treating the symptoms while remaining blissfully, almost willfully, ignorant of the underlying disease.
They speak of "memory pressure" and "garbage collection pauses" as if these are unavoidable laws of nature, like thermodynamics or student apathy during an 8 AM lecture on B-trees. My dear boy, a properly designed database system manages its own memory. It doesn't outsource this most critical of tasks to a non-deterministic, general-purpose janitor that periodically freezes the entire world to tidy up. The fact that your primary concern is placating the Javanese deity of Garbage Collection before it smites your precious "cluster" with a ten-second pause is not a sign of operational rigor; it's a foundational architectural flaw. It is an admission of defeat before the first query is even executed.
But of course, one cannot expect adherence to first principles from a system that treats the relational model as a quaint historical artifact. They've replaced the elegant, mathematically-sound world of normalized forms and relational algebra with a glorified key-value store where you just... dump your JSON and pray. One imagines Edgar Codd weeping into his relational calculus. They've abandoned the guaranteed integrity of a well-defined schema for the fleeting convenience of "schema-on-read," which is a delightful euphemism for "we have no idea what's in here, but we'll figure it out later, maybe." It's a flagrant violation of Codd's Information Rule, but I suppose rules are dreadfully inconvenient when you're trying to move fast and break things. Mostly, it seems, you're breaking the data's integrity.
And the way they discuss their distributed architecture! They speak of shards and replicas as if they've discovered some new cosmological principle. In reality, they're just describing a distributed system that plays fast and loose with the 'C' and the 'I' in ACID. They seem to have stumbled upon the CAP theorem, not by reading Brewer's work, but by accidentally building a system that kept losing data during network hiccups and then retroactively labeling its "eventual consistency" a feature.
"Monitor your cluster health..."
Of course you must! When you've forsaken transactional integrity, you are no longer managing a database; you are the frantic zookeeper of a thousand feral data-hamsters, each scurrying in a slightly different direction. You have to "monitor" it constantly because you have no mathematical guarantees about its state. You're replacing proofs with dashboards. Clearly they've never read Stonebraker's seminal work on the "one size fits all" fallacy. They've built a system that's a mediocre search index and a truly abysmal database, excelling at neither, and they've surrounded it with an entire cottage industry of "monitoring solutions" to watch it fail in real-time.
It's all so painfully clear. They don't read the papers. They read blog posts written by other people who also don't read the papers. They are trapped in a recursive loop of shared ignorance, celebrating their workarounds for self-inflicted problems. They're not building on the shoulders of giants; they're dancing on their graves.
This isn't computer science. This is digital plumbing. And forgive me, but I have a lecture to prepare on third normal form—a concept that will still be relevant long after the last Elasticsearch cluster has been garbage-collected into oblivion.
Alright, hold my lukewarm coffee. I just read this masterpiece of marketing masquerading as a technical document. "The business impact of Elasticsearch logsdb index mode and TSDS." Oh, I can tell you about the business impact, alright. The business impact is me, Alex Rodriguez, losing what's left of my hairline at 3 AM on Labor Day weekend.
They talk about significant performance improvements and storage savings. Of course they do. Every vendor presentation starts with these slides. They show you a graph that goes up and to the right, generated in a pristine lab environment with perfectly formatted data and zero network latency. It’s beautiful. It's also a complete fantasy.
My "lab environment" is a chaotic mess of a dozen microservices, all spewing logs in slightly different, non-standard JSON formats because one of the dev teams decided to “innovate” on the logging schema without telling anyone. This new "logsdb index mode" sounds fantastic for their sanitized, perfect-world data. I'm sure it’ll handle our real-world garbage heap of logs with the same grace and elegance as a toddler with a bowl of spaghetti. The "performance improvement" will be a catastrophic failure to parse, followed by the entire cluster's ingest pipeline grinding to a halt.
And TSDS. Time Series Data Streams. It's so revolutionary. It's just a new way to shard by time, which we've been hacking together with index lifecycle policies and custom scripts for a decade. But now it's a productized solution, which means it has a whole new set of undocumented failure modes and cryptic error messages.
They claim it offers "reduced complexity."
Let me translate that for you. It reduces complexity for the PowerPoint architects who don't have to touch a command line. For me, it means I now have two systems to debug instead of one. When it breaks, is it the old ILM policy fighting with the new TSDS manager? Is the logsdb mode incompatible with a specific Lucene segment merge strategy that only triggers when the moon is in gibbous-waning phase? Who knows! The documentation will just be a link to a marketing page.
And the best part, my absolute favorite part of every one of these "next-gen" rollouts, is the complete and utter absence of any meaningful discussion on monitoring.
logsdb compaction process gets stuck in a loop and starts eating 100% of the CPU on my data nodes? Probably after the CEO calls me asking why the website is down.No, no. Monitoring is an afterthought. We'll get a blog post about "Observing Your New TSDS Clusters" six months after everyone has already adopted it and suffered through three major outages.
So here’s my prediction. We’ll spend two sprints planning the "zero-downtime migration." The migration will start at 10 PM on a Friday. The first step, re-indexing a small, non-critical dataset, will work flawlessly. Confidence will be high. Then, we’ll hit the main production cluster. The script will hang at 47%. The cluster will go yellow. Then red. The "seamless fallback plan" will fail because a deprecated API was removed in the new version.
And at 3 AM, on a holiday weekend, I’ll be sitting here, mainlining caffeine, staring at a Java stack trace that’s longer than the blog post itself. The root cause will be some obscure interaction between the new TSDS logic and our snapshot lifecycle policy, causing a cascading failure that corrupts the cluster state. The final "business impact" won't be a 40% reduction in storage costs; it’ll be a 12-hour global outage and my undying resentment.
But hey, at least I’ll get a cool new sticker for my laptop lid. I'll put it right between my ones for CoreOS and RethinkDB. Another fallen soldier in the war for "reduced complexity." Bless their hearts.
Oh, this is precious. "In the hopes that it saves someone else two hours later." Two hours. That's cute. That's the amount of time it takes for the first pot of coffee to go cold during a real incident. Two hours is what the sales engineer promises the entire "fully-automated, AI-driven, zero-downtime migration" will take. This blog post isn't just about an ISP; it's a perfect, beautiful microcosm of my entire career.
You see, that line right there, “Astound supports IPv6 in most locations,” I’ve seen that lie in a thousand different pitch decks. It’s the same lie as "Effortless Scalability" from the database that can't handle more than 100 concurrent connections. It's the same lie as "Seamless Integration" from the monitoring tool that needs a custom-built Golang exporter just to tell me if a disk is full. "Most locations" is corporate doublespeak for one specific rack in our Washington data center that our founder’s nephew set up as a summer project in 2017.
And the tech support agents? Perfect. Absolutely perfect. This is the vendor's "dedicated enterprise support champion" on the kickoff call.
“Yes, we do support both DHCPv6 and SLAAC… use a prefix delegation size of 60.”
I can hear him now. “Oh yes, Alex, our new database cluster absolutely supports rolling restarts with no impact to the application. Just toggle this little 'graceful_shutdown' flag here. It’s fully documented in the appendix of a whitepaper we haven't published yet.”
And there you are, just like this poor soul, staring at tcpdump at 2 AM, watching your plaintive requests for an address vanish into the void. For me, I'm not looking at router requests; I'm tailing logs, watching the leader election protocol have a seizure because the "graceful shutdown" was actually a kill -9. I'm watching the replication lag climb to infinity because "most locations" apparently didn't include our primary failover region in us-east-2.
And the monitoring? Don't even get me started. Of course, the main dashboard is a sea of green. The health check endpoint is returning a 200 OK. The vendor’s status page says "All Systems Operational". Why? Because we're monitoring that the process is running, not that it's actually doing anything useful. We're checking if the patient has a pulse, not if they're screaming for help. We'll get around to building a meaningful check for v6 connectivity or actual data replication after the post-mortem, right next to the action item labeled "Investigate Monitoring Enhancements - P3."
Every time I see a promise like this, I just reach for my laptop lid and find a nice, empty spot. This "Astound" ISP deserves a sticker right here next to my collection from QuerySpark, CloudSpanner Classic, and HyperClusterDB—all ghosts of architectures past, all promising a revolution, all delivering a page at 3 AM.
I can see it now. It'll be Labor Day weekend. Some new, critical, IPv6-only microservice for payment processing will be deployed to the shiny new cluster that's running in a "cost-effective" data center. The one the VP signed a three-year deal on because their golf buddy is the CRO of Astound. Everything will work perfectly in staging. Then, at 3:17 AM on Saturday, the primary node will fail. The system will try to fail over to the DR node. The one that's not in Washington.
And as the entire company's revenue stream grinds to a halt because we can't get a goddamn IP address, I'll be there, tcpdump running, muttering to myself, "but they told me to use a prefix delegation size of 60."
Well, look at this. Another blog post from the Mothership, solving a problem I’m sure kept all those content leads up at night: "creative fatigue." I remember when we just called that "writer's block" and solved it with coffee and a deadline, but I guess that’s not billable. And they've got a statistic to prove it's a real crisis! A whole 16% of content marketers struggle with ideas. Truly, a challenge worthy of a "transformative solution" built on a spaghetti of microservices.
Let’s talk about this "flexible data infrastructure," shall we? Because I remember the meetings where "flexibility" was the keyword we used when the product couldn't handle basic relational constraints.
Developing an AI-driven publishing tool necessitates a system that can ingest, process, and structure a high volume of diverse content from multiple sources. Traditional databases often struggle with this complexity.
Struggle with the complexity. That’s a polite way of saying "we don't want to enforce a schema because that requires planning." The joy of a flexible schema isn't for the developer; it's for the salesperson. It means you can throw any old JSON garbage into a "collection" and call it a day. Then, six months later, when you have three different fields for authorName, writer_id, and postedBy, and no one knows which is the source of truth, that’s when the real fun begins. That’s not a feature; it’s technical debt sold as innovation.
And look at that beautiful diagram! All those neat little boxes and arrows. It’s missing a few, though. There should be one for the DevOps team frantically trying to keep the Kubernetes cluster from imploding under the weight of all these "endpoints." And another box for the finance department, staring at the Atlas bill after "continuously updating from external APIs" all month. Ingest, process, and structure is a very clean way to describe "hoard everything and pray your aggregation pipeline doesn't time out."
Speaking of which, Atlas Vector Search is the star of the show now, isn't it? It's amazing what you can accomplish when you slap a marketing-friendly name on a Faiss index and call it revolutionary. It "enables fast semantic retrieval." What this means is you can now search your unstructured, inconsistent data swamp with even more ambiguity. You don’t find what you’re looking for, you find what a machine learning model thinks is "similar." Enjoy debugging that when a user searches for "quarterly earnings report" and gets back a Reddit post about chicken nuggets.
But my absolute favorite part, the real work of comedic genius here, is this claim about "Solving the content credibility challenge." How, you ask, do they achieve this monumental feat in an age of rampant misinformation?
They store the source URL.
That's it. That's the solution. They save a hyperlink in a document. This isn't a credibility engine; it's a bookmarking feature from 1998. The idea that this somehow guarantees trustworthy content when the LLM assistant is probably hallucinating half its sources anyway is just… chef’s kiss. They’re not solving the credibility problem; they're just giving you a link to the scene of the crime.
Let’s be honest about what’s really happening "behind-the-scenes":
userProfiles collection is a minefield of PII that would make any GDPR consultant’s eye twitch.drafts collection means version control is an absolute nightmare, managed by ad-hoc fields like draft_v2_final_REAL_final.So yes, by all means, build your entire editorial operation on this. Embrace the "spontaneous and less dependent on manual effort" future. Just know that what they call an "agile, adaptable and intelligent" system, those of us who built and maintained it called it "schema-on-scream."
It’s not about automation; it’s about lock-in. It's about turning a marketing problem into an engineering nightmare you pay for by the hour. So go on, solve your "creative fatigue." The rest of us who've seen the query plans will stick to a notepad and a decent search engine.
Oh, this is just wonderful. A new release to circle on my calendar. I'll be sure to mark September 15th right next to my quarterly budget review, as a little reminder of what innovation looks like. It’s so refreshing to see a solution that solves "real operational headaches." The headaches I get from reading my P&L statement are, I assume, not on the roadmap.
I especially admire the promise of solving these headaches "without the licensing restrictions or unpredictable costs you face with Redis." That’s a truly admirable goal. It's like offering someone a "free" puppy. The initial acquisition cost is zero, which looks fantastic on a spreadsheet. It’s the subsequent "unpredictable costs"—the food, the vet bills, the chewed-up furniture, the emergency surgery after it swallows a sock—that tend to get lost in the marketing material.
They say it's a fork and that the "same engineers who built Redis" are now on board. That's lovely. It gives me great confidence to know the people who built the house we're currently living in have now built a new, very similar house next door and are encouraging us to move. They're even leaving the door unlocked for us. How thoughtful. They just neglect to mention the cost of packing, hiring the movers, changing our address on every document we own, and discovering the plumbing in the new place is subtly different in a way that requires an entirely new set of wrenches.
Let’s do some quick, back-of-the-napkin math on the Total Cost of Ownership for this "free" software.
So, to save on "unpredictable" licensing fees, we've proactively spent nearly half a million dollars. It's a bold financial strategy, one might say. It’s a bit like preemptively breaking your own leg to save on future skiing expenses.
If you’ve been following Valkey since it forked from Redis, this release represents a major milestone.
It certainly is a milestone. It’s the point where a free alternative becomes expensive enough to warrant a line item in my budget titled "Miscellaneous Unforced Errors." The promise of enterprise-grade features is the cherry on top. I’ve been a CFO for twenty years; I know that "enterprise-grade" is just a polite way of saying “You will now require a dedicated support contract and a team of specialists to operate this.”
So, yes, thank you for the announcement. I've circled September 15th on my calendar. I’ve marked it as the day I'm taking my finance team out for a very expensive lunch, paid for by the "unpredictable licensing fees" we'll continue to pay our current vendor. Funny how predictable those costs suddenly seem.