Amazon Enterprise Search: Kendra

December 6, 2019

Years ago I worked on a small project for a company connected to the film industry. At one of those Hollywood “lunches”, a person pointed across the restaurant and said, “That’s Kendra.” I had zero idea who or what a Kendra was. It turned out that “Kendra” was famous, a star. She was a Playboy bunny! She looked like most of the other female appearing types in the room.

Amazon’s Kendra is not a Playboy bunny. Kendra is Amazon’s new online enterprise search service. It looks pretty much like all the other online enterprise search services in the room.

There’s a difference. This enterprise search service is mounted on the Amazon platform, and it has open source goodness, some proprietary fashion flair, and hooks into numerous good looking advanced AWS services.

Amazon says in “Amazon Kendra”:

Amazon Kendra is a highly accurate and easy to use enterprise search service that’s powered by machine learning. Kendra delivers powerful natural language search capabilities to your websites and applications so your end users can more easily find the information they need within the vast amount of content spread across your company.

I am not sure what “accurate” means, but it sure differentiates the service from the odd ball results some enterprise search solutions deliver. The “easy” part is also relative and subjective. Which of AWS’s more than 170 functions and services does Kendra get along with? Too soon to tell.

Some observations:

  • The enterprise search vendors who have convinced venture capitalists to invest hundreds of millions in enterprise search and retrieval may be curious about Amazon’s sudden aggressiveness
  • The enterprise search companies themselves now have to decide: Put services on AWS or go elsewhere despite the costs and resources required
  • The AWS customers may want to kick the tires of the AWS service and postpone a procurement of a venture funded old school search engine. (Talking about NLP and machine learning is one thing. Delivering productized services from an AWS dashboard is another.)

Net net: For organizations struggling to federate and provide blockchain centric information access management, Amazon’s Kendra might look quite fetching.

Stephen E Arnold, December 6, 2019

ElasticSearch: A Push for Log File Revenue?

November 13, 2019

Elasticsearch had a moment in the sun. For several years it was the go to way to deploy a low cost, reasonably usable search and retrieval system. Then came the venture funding to a clump of outfits talking about search in terms of jargon that would have made a 1950s’ Madison Avenue executive reach for the bottle in his desk drawer.

To get a sense of the pressure exerted on ElasticSearch, navigate to “How to Get Started with Kibana.” Why battle with the tens of millions in fresh cash stuffing the pockets of Algolia, Coveo, and LucidWorks, among other 21st century enterprise search vendors with a penchant for buzzwords?

Do the pivot and keep one’s hand on the Elasticsearch throttle.

The write up explains:

Kibana is a powerful tool for visualizing data in Elasticsearch.

The article provides a sunny overview of how

you can explore practically any type of data, from text documents to machine logs, application metrics, ecommerce traffic, sensor telemetry, or your company’s business KPIs.

A KPI is, if you did not know, is a key performance indicator. What’s performance? What’s key? Heck, what’s an indicator? There you go. Modern methods for Kibana.

Net net: Elasticsearch is making it clear that it too is moving beyond search.

Search, however, has been moving beyond itself for decades. But my tagline for anything to do with the interesting and slightly sordid past of enterprise search is, “Who cares?”

Elasticsearch stakeholders.

Stephen E Arnold, November 13, 2019

Coveo: A 15 Year old $1 Billion Start Up Unicorn in Canada!

November 6, 2019

I read “Coveo Raises US$172M at $1B+ Valuation for AI-Based Enterprise Search and Personalization.” The write up states:

Search and personalization services continue to be a major area of investment among enterprises, both to make their products and services more discoverable (and used) by customers, and to help their own workers get their jobs done, with the market estimated to be worth some $100 billion annually. Today, one of the big startups building services in this area raised a large round of growth funding to continue tapping that opportunity.

Like Elastic, Algolia, and LucidWorks, Coveo is going to have to generate sufficient revenues to pay back its investors. Perhaps the early supporters have cashed out, but the new money is betting on the future.

Coveo was founded in Quebec City more than a decade ago. The desktop search company Copernic spun off Coveo in 2004. The original president was Laurent Simoneau. Mr. Tetu is an investor with great confidence in enterprise software, and he has become the “founder”, according to the write up. In April 2018, Coveo obtain about $100 million from Evergreen Coast Capital.

DarkCyber recalls that Coveo has moved from Microsoft-centric search to search as a service to customer experience and now personalization.

In 2005, I wrote this about the upsides of the Coveo approach in the Enterprise Search Report I compiled for an outfit lost to memory:

Coveo is a reasonably-priced, stable product. Any organization with Microsoft search will improve access to information with a system like Coveo’s. Microsoft SharePoint customers will want to do head-to-head comparisons with other “solutions” to Microsoft’s native search solution. Coveo has a number of features that make it a worth contender. Other benefits of the Coveo approach include:

  • Web-based administration tool allows straightforward configuration and monitoring of the system.
  • Automatic indexing of new and updated documents in near real-time.
  • Includes linguistic and statistical technologies that can identify the key concepts and the key sentences of indexed documents. Provides automated document summaries for faster reading and filtering.
  • Groups information sources into collections for field-specific searches.
  • The product is attractively priced.
  • Tightly integrated with other Microsoft products and Windows-based security regimes.
  • Customer base has grown comparatively quite rapidly and customers tend to speak well of the product.

I noted these considerations:

The software is Windows-centric – both in terms of its own software as well as document security settings it tracks – which may be an issue with certain types of organizations. You will have to assign permissions to index to allow the ASP.NET worker process user to access the index. The task is simplified, but it can be overlooked. Administrative controls are presented without calling attention to actions that require particular attention. Coveo is still however able to search content on any operating system, application, or server. Other drawbacks of the Coveo search system include:

  • There is limited software development support to allow customization or extensions of the core technology to other applications, although the company is expanding the product’s reach through Dot Net-based APIs.
  • When the system is installed and its defaults accepted, the “Everyone” group is enabled. Administrators will want to customize this setting. A wizard would be a useful option for organizations new to enterprise search.
  • No native taxonomy support, except through partner Entrieva.
  • Achieving scalability beyond hundreds of millions of documents requires appropriate resources.

My final take on the company was:

Coveo Enterprise Search meets many distinct needs of the small and medium-sized business that has standardized on the Microsoft platform, while still providing a few critical advanced search capabilities. Perhaps more importantly, CES minimizes search training, system maintenance, and other cost “magnets” that typically accompany an enterprise search deployment.
Like a handful of other products in this report, you can test Coveo out first, via a free download of a document-limited version.

The challenge for Copernic is to make enough sales and to generate robust sustainable income. This is the uphill run that Algolia, Elastic, LucidWorks, and probably a number of other enterprise search vendors face. Perhaps an outfit like Xerox will buy up, which would be one way to get the investors their money?

DarkCyber wishes Coveo the best. But a start up unicorn? No, that is not exactly correct for a 15 year old outfit. This push to make the investors smile is not for the faint hearted or those who have a solid grasp of the formidable enterprise search options available today. Plus there are outfits like Diffeo and other next generation information access systems available for free (Eleasticsearch) or bundled with other sophisticated information management tools (Amazon, search, managed blockchain, workflows, and a clever approach to vendor lock in.)

One tip: Don’t visit Quebec City in February during a snow storm.

Stephen E Arnold, November 6, 2019

Stephen E Arnold, November 5, 2019

Enterprise Search: Two Interesting Assertions

September 23, 2019

Judging from the uptick in the estimates of the size of the enterprise search market, the “find documents” purveyors are generating public relations outputs.

Two items DarkCyber found interesting:

LucidWorks occupies a position of distinction. The company is the “sole visionary” in the enterprise search universe. According to “one of the world’s leading independent technology research and advisory firms,” LucidWorks — now check this wording — “LucidWorks believes its strong product offering and clear understanding of the needs of enterprise buyers in the Insight Engine market will enable the company to serve a wide variety of industries well into the future.” For more of this “alone at the top” razzmatazz, navigate to this Yahoo news item.

The second item is a bit more modest. Economic Times reported this fascinating factoid:

iQuanti is rapidly building its customer success and solutions teams in the region to activate its growth plans. Meanwhile, globally, iQuanti’s patented enterprise search channel platform ALPS was named the second-best search software in the U.S by the Drum Search Awards in 2018. ALPS uses proprietary data science and machine learning models to build predictive enterprise-level roadmaps that deliver strong ROI. iQuanti has also featured in the 2019 Inc. list of fastest-growing private companies in the US, for a record fifth time.

DarkCyber assumes that the top search engine is LucidWorks.

Now you know or maybe not.

Stephen E Arnold, September 23, 2019


Can a Well Worn Compass Help Enterprise Search Thrive?

September 4, 2019

In the early 1990s, Scotland Yard (which never existed although there is a New Scotland Yard) wanted a way to make sense of the data available to investigators in the law enforcement sector.

A start up in Cambridge, England, landed a contract. To cut a multi year story short, i2 Ltd. created Analyst’s Notebook. The product is now more than a quarter century old, and the Analyst’s Notebook is owned by IBM. In the span of five or six years, specialist vendors reacted to the Analyst’s Notebook functionalities. Even though the early versions were clunky, the software performed some functions that may be familiar to anyone who has tried to locate, analyze, and make sense of data within an organization. I am using “organization” in a broad sense, not just UK law enforcement, regulatory enforcement, and intelligence entities.

What were some of the key functions of Analyst’s Notebook, a product which most people in the search game know little about? Let me highly a handful, and then flash forward to what enterprise search vendors are trying to pull off in an environment which is very different from what the i2 experts tackled 25 years ago. Hint: Focus was the key to Analyst’s Notebook’s success and to the me-too products which are widely available to LE and intel professionals. Enterprise search lacks this singular advantage, and, as a result, is likely to flounder as it has for decades.

The Analyst’s Notebook delivered:

  • Machine assistance to investigators implemented in software which generally followed established UK police procedures. Forget the AI stuff. The investigator or a team of investigators focused on a case provided most of the brain power.
  • Software which could identify entities. An entity is a person, place, thing, phone number, credit card, event, or similar indexable item.
  • Once identified, the software — influenced by the Cambridge curriculum in physics — could display a relationship “map” or what today looks like a social graph.
  • Visual cues allowed investigators to see that a person who received lots of phone calls from another person were connected. To make the relationship explicit, a heavy dark line connected the two phone callers.
  • Ability to print out on a big sheet of paper these relationship maps and other items of interest either identified by an investigator or an item surfaced using maths which could identify entities within a cluster or an anomaly and its date and time.

Over the years, other functions were added. Today’s version offers a range of advanced functions that make it easy to share data, collaborate, acquire and add to the investigative teams’ content store (on premises, hybrid, or in the cloud), automate some functions using IBM technology (no, I won’t use the Watson word), and workflow. Imagery is supported. Drill down makes it easy to see “where the data came from.” An auditor can retrace an investigator’s action in order to verify a process. If you want more about i2, just run a Bing, Google, or Yandex query.

Why am I writing about decades old software?

The reason is that is read an item from my files as my team was updating my comments about Amazon’s policeware for the October TechnoSecurity & Digital Forensics Conference. The item I viewed is titled “Thomson Reuters Partners with Squirro to Combine Artificial Intelligence Technology and Data to Unlock Customer Intelligence.” I had written about Squirro in “Will Cognitive Search (Whatever That Is) Change Because of Squirro?

I took a look at the current Squirro Web site and learned that the company is the leader in “context intelligence.” That seemed similar to what i2 delivered in the 1990s version of Analyst’s Notebook. The software was designed to fit the context of a specific country’s principal police investigators. No marketing functions, no legal information, no engineering product data — just case related information like telephone records, credit card receipts, officer reports, arrest data, etc.

Squirro, founded in 2012 or 2013 (there are conflicting dates online) states that the software delivers

a personalized, real-time contextual stream from the sea of information directly to your workplace. It’s based on Squirro’s digital fingerprint technology connecting personal interests and workflows while learning and refining as user interactions increase.

I also noted this statement:

Squirro combines all the different tools you need to work with unstructured data and enables you to curate a self-learning 360° context radar natural to use in any enterprise system. ‘So What?’ Achieving this reduces searching time by 90%, significantly cutting costs and allows for better, more effective decision-making. The highly skilled Swiss team of search experts has been working together for over 10 years to create a precise context intelligence solution. Squirro: Your Data in Context.

Well, 2013 to the present is six years, seven if I accept the 2012 date.

The company states that it offers “A.I.-driven actionable Insights,” adding:

Squirro is a leading AI-platform – a self-learning system keeping you in the know and recommending what’s next.

I’m okay with marketing lingo. But to my way of thinking, Squirro is edging toward the i2 Analyst’s Notebook type of functionality. The difference is that Squirro wants to serve the enterprise. Yep, enterprise search with wrappers for smart software, reports, etc.

I don’t want to make a big deal of this similarity, but there is one important point to keep in mind. Delivering an enterprise solution to a commercial outfit means that different sectors of the business will have different needs. The different needs manifest themselves in workflows and data particular to their roles in the organization. Furthermore, most commercial employees are not trained like police and intelligence operatives; that is, employees looking for information have diverse backgrounds and different educational experiences. For better or worse, law enforcement intelligence professionals go to some type of training. In the US, the job is handled by numerous entities, but a touchstone is FLETC. Each country has its equivalent. Therefore, there is a shared base of information, a shared context if you will.

Modern companies are a bit like snowflakes. There’s a difference, however, the snowflakes may no longer work together in person. In fact, interactions are intermediated in numerous ways. This is not a negative, but it is somewhat different from how a team of investigators worked on a case in London in the 1990s.

What is the “search” inside the Squirro information retrieval system? The answer is open source search. The features are implemented via software add ons, wrappers, and micro services plus other 2019 methods.

This is neither good nor bad. Using open source reduces some costs. On the other hand, the resulting system will have a number of moving parts. As complexity grows with new features, some unexpected events will occur. These have to be chased down and fixed.

New features and functions can be snapped in. The trajectory of this modern approach is to create a system which offers many marketing hooks and opportunities to make a sale to an organization looking for a solution to the ever present “information problem.”

My hypothesis is that i2 Analyst’s Notebook succeeded an information access, analysis, and reporting system because it focused on solving a rather specific use case. A modern system such as a search and retrieval solution that tries to solve multiple problems is likely to hit a wall.

The digital wall is the same one that pushed Fast Search & Transfer and many other enterprise search systems to the sidelines or the scrap heap.

Net net: Focus, not jargon, may be valuable, not just for Squirro, but for other enterprise search vendors trying to attain sustainable revenues and a way to keep their sources of funding, their customers, their employees, and their stakeholders happy.

Stephen E Arnold, September 4, 2019

The New Lingo of Enterprise Search

August 28, 2019

Enterprise search is back. My Google Alert has been delivering market research reports which tell me that finding information is huge. Plus, there have been some announcements about funding which have surprised me. Examples include:

  • Capacity raised $13.2 million. Source: DarkCyber
  • LucidWorks snagged an additional $100 million. Source: Globe News Wire
  • Squirro pulled in additional funds, but the timing of the Salesforce investment and additional funding of this Zurich based company remains a bit of a mystery. Source: Venture Lab

These are just three examples plucked from my box of note cards about search vendors.

What’s interesting is the lingo, the jargon, and the argot these outfits are using. Frankly the plumbing is usually open source, a fact which the companies bury beneath the blizzard of buzzwords.

Here are some examples:

AI powered

actionable insights

artificial intelligence



connect the dots

data mining


information mining

machine learning

natural language

pattern detection


self learning


The problem with the vendors collecting investment funds are easy to identify:

  1. The content processed is text. The unstructured information in videos, podcasts, messaging apps like WhatsApp, images like chemical structures and engineering drawings, etc. are not included.
  2. Indexing content residing on cloud platforms may work today, but as market dynamics shift, access to that content my be blocked or prohibited by regulations in certain countries
  3. Federation, on-the-fly so that real time information is available remains a challenge which typically requires script fiddling or new content filters
  4. Configuration of “smart” systems is not significantly different from the complex, time consuming, and expensive procedures which added friction to some Autonomy, Convera, Fast Search & Transfer, and similar systems’ deployment
  5. Maintenance is an issue, micro services work well in a low latency environment. Under loads, the magic of sub three second response can disappear
  6. Search remains an idiosyncratic solution. Many departments require specific features. As a result, enterprise search — regardless of the wrappers around open source information retrieval systems — is a series of customizations.

To sum up, enterprise search has failed to deliver for more than 50 years. Despite the optimism that investors have for “finding the next Google”, enterprise search vendors will find themselves hitting a revenue ceiling just as Autonomy, Fast Search, and similar firms did.

The fix was acquisitions and allegations of financial fancy dancing. If we assume that investors still dream of a 10x or higher return, is it possible that LucidWorks can generate sufficient revenue to pull off an IPO or a sale like Exalead, Vivisimo, and other search vendors were able to complete before the hammer fell?

This is an important question because new enterprise search vendors are popping up like mushrooms. The incumbents like Attivio, Coveo, Mindbreeze, and Sinequa are also trying to smash a ball over the fence.

Net net: Enterprise search appears to be putting on the worn slippers last used by the founders of Fast Search & Transfer. Maybe Microsoft will buy another enterprise search vendor? The problem is that enterprise search is easy to make visible with marketing LED lights. Delivering sustainable revenues is a far greater challenge when Amazon is a competitor and a platform enabler.

What happens when Amazon competes more aggressively, raises its prices, or bundles text search into another of its services?

Answer: Nothing particularly beneficial for the investors in new and improved enterprise search solutions based on Lucene/Solr and dusted with disco glitter.

Stephen E Arnold, August 28, 2019

Enterprise Search: AI and a Low Spend

August 26, 2019

DarkCyber Read “Capacity Raises $13.2 Million to Index Emails, Files, and More with AI.” The company was founded in 2017. We noted this passage:

Capacity (formerly, [is] a startup developing a platform that indexes data from apps, teams, and more and enables users to search through the corpus using natural language.

Plus, the system learns and improves over time.

The company’s funding to deliver AI, multi-source enterprise search is “over $21 million.”

One of the founders is CEO David Karandish, formerly the CEO of He is quoted as saying:

[Capacity] is an intuitive, intelligent AI-powered Teammate who gives employees instant access to the information they need to do their jobs well.

The indexing system can process content from such systems as:

  • ADP human resource information
  • Box
  • NetSuite
  • Google Gmail
  • Microsoft Exchange
  • Microsoft OneDrive
  • Sage human resource information
  • Salesforce
  • ServiceNow
  • Zendesk

The system includes “a chatbot with natural language processing capabilities that integrates with popular messaging apps such as Slack and Skype.”

We noted this statement:

Capacity can deliver company-wide announcements, like daily news and event notifications, and onboard new hires by providing access to forms that need to be completed. For customers with websites that have FAQ sections, it can be made public-facing to help cut down on customer service requests.

If Capacity can deliver, outfits like LucidWorks will have some explaining to do to its investors.

Stephen E Arnold, August 26, 2019

Enterprise Search and Grease Management

June 7, 2019

I see some crazy stuff. Every once in a while, a really crazy item crosses my desk. The example I wish to highlight today is called “Enterprise Search Software Market to depict huge growth, Key Methodologies, Top Players: SharePoint, IBM, Lucidworks, Microsoft FAST, Oracle, Amazon CloudSearch, Apache Lucene, Attivio.” My hunch is that rolling in Amazon and Microsoft cloud revenues will make almost any market look like Popeye the Sailor Man. The reality is that enterprise search came and went in a blaze of litigation and embarrassment. Some of the exhaust seems to be emanating from the Hewlett Packard litigation related to the former medical device maker’s acquisition of an enterprise search vendor.

Enterprise search has overpromised and under delivered for about 50 years. Elsewhere I have recounted the adventures of services which most people don’t recall or simply knew nothing about. Remember InQuire, the service with forward truncation? A more recent fumble is the disappearance of those cheerful yellow Google Search Appliances, its staff, and the marketing collateral promising an end to the misery of traditional enterprise search solutions.

The buzz has not died down at at Reports Monitor. You can read their remarkable news release at this link. Forget the incredible hyperbole of “huge growth.” Hello, Reports Monitor, one can download a perfectly good enterprise search system from open source repositories. There are low cost systems available from outfits like Funnelback. You can get a next generation system from vendors of intelware. Don’t recognize the term? Don’t worry. These vendors don’t know what enterprise search means. And there are some companies which this report does not list as players. Want these names? Sorry, that’s information for which I charge a fee. Believe me. Reports Monitor and perhaps you, gentle reader, don’t know about these companies either.

What causes me to write about a report which is a bit on the wild side? How about this passage:

Key Insights:

  • Complete in-depth analysis of the Grease Management in Commercial Kitchens
  • Important changes in market dynamics.
  • Segmentation analysis of the market.
  • Emerging segments and regional markets.
  • Historical, on-going, and projected market analysis based on volume and esteem.
  • Assessment of niche industry players.
  • Market share analysis.
  • Key strategies of major players.

Yep, grease management. Now we’re getting to the heart of slippery data and even more slippery reports about enterprise search. The report provides region-wise data. Great stuff.

News flash: Enterprise search left the dock and took on water. Some outfits torpedoed their investors, customers, and partners. Others have tried to become business intelligence, analytics, even customer service support systems. Did not work too well.


Enterprise search is not a general purpose application. Significant work is necessary to make it possible for employees to find information in what are silos or in oddball lingo. Furthermore important people like lawyers, product researchers, and big wheels like to keep their information secret. An enterprise search system has failure baked in unless it is tailored to a quite specific problem. But at that point why not buy an eDiscovery system, a lab notebook system, or a niche solution for the eager beavers in marketing?

Maybe I am too harsh on the grease management angle. That may be closer to the truth than Reports Monitor realizes.

Stephen E Arnold, June 7, 2019

Amazon Moved a Knight. Google Pushes a Pawn

April 10, 2019

If you care about search and retrieval, you may be interested in the chess game underway between Amazon and Google. Amazon seized the initiative by embracing the open source Elasticsearch. Google, an outfit whose failures in search are known to anyone who licensed a Google Search Appliance, has responded. The pawn Google nudged forward is Elastic, the outfit which has been a big dog in search and retrieval for several years.

According to “Elastic and Google Cloud Expand Elasticsearch Service Partnership”:

Elastic (NYSE: ESTC) and Google Cloud (GCP) announced the expansion of their managed Elasticsearch Service partnership to make it faster and easier for users to deploy Elasticsearch within their Google Cloud Platform (GCP) accounts. Building upon the partnership to deliver Elastic’s Elasticsearch Service on GCP, the companies announced a fully managed, cloud-native integration for discovery, billing, and support for Elasticsearch Service within the GCP Console.

We also circled this statement, which is quite fascinating when interpreted in the context of Amazon’s open source tactic:

Elastic’s Elasticsearch Service on GCP gives users a turnkey experience to deploy powerful Elastic Stack features of Elasticsearch and Kibana, including proprietary free and paid features such as security, alerting, machine learning, Kibana spaces, Canvas, Elasticsearch SQL, and cross-cluster search. In addition, users can deploy new curated solutions for logging, infrastructure monitoring, mapping and geospatial analysis, and APM; optimize compute, memory, and storage workloads using Elastic’s customizable deployment templates such as hot-warm architecture for the logging use case; and upgrade to the latest version of Elasticsearch and Kibana as soon as it is released with a single click.

The chess timer is Amazon’s. Will the company make a lucid move?

Stephen E Arnold, April 10, 2019

The Search Wars: When Open Starts to Close

March 12, 2019

Compass Search. The precursor. The result? Elasticsearch. No proprietary code. Free and open source. The world of enterprise search shifted.

As a result of Shay Bannon’s efforts, an alternative to proprietary search and interesting financial maneuvers, an individual or organization could download code and set up a functional enterprise search system.

There are proprietary search systems available like Coveo. But most of the offerings are sort of open sourcey. It is a marketing ploy. The forward leaning companies do not use the word search to market their products because zippier functionality is what brings tire kickers and some buyers.

The landscape of search seems to be doing its Hawaii volcano act. No real eruption buts shakes, hot gas, and cracks have begun to appear. The lava flows will come soon enough.

a bezos art

The path is clear to the intrepid developer.

The tip off is Amazon’s announcement that it now offers an open distro for Elasticsearch. Why is Amazon taking this step? The company explains:

Elasticsearch has become an essential technology for log analytics and search, fueled by the freedom open source provides to developers and organizations. Our goal is to ensure that open source innovation continues to thrive by providing a fully featured, 100% open source, community-driven distribution that makes it easy for everyone to use, collaborate, and contribute.

DarkCyber’s briefings about Amazon’s policeware initiative suggest that the online bookstore is adding another component to its robust intelligence system and services.

The move involves or will involve:

  • Entrepreneurs who will see Amazon as creating low friction for new products and services
  • Partners because implementing search can be a consulting gold mine
  • Users
  • Developers who will use an Amazon “off the shelf” solutions
  • Competitors who may find the “other open source” Elasticsearch lagging behind the Amazon “house brand”.

The move is not much of a surprise. Amazon seeks to implement its version of IBM’s 1960s style vendor lock in. Open source is open source, isn’t it? A version of the popular Elasticsearch system which has utility in commercial products to add ons which help make log files more mine-able. Plus search snaps into the DNA of the Amazon jungle of services, functions, features, and services. Where there is confusion, there are opportunities to make money.

Adding a house brand to its ecosystem is a basic tactic in the Amazon playbook. Those T shirts with the great price are Amazon’s, not the expensive stuff with a fancy brand name. T shirts and search? Who cares?

What’s the play mean for over extended proprietary search systems which may never generate a pay day for investors? A lot of explaining seems likely.

What the play mean for Elastic, the company which now operates the son of Compass Search? Some long off site meetings may be ahead and maybe some chats with legal eagles.

What’s the play mean for vendors using Amazon as back end plumbing for their enterprise or policeware services? A swap out of the Elasticsearch system for the Amazon version could be in the cards. Amazon Elasticsearch will probably deliver fewer headaches and lost weekends than using the Banon-Elastic version. Who wants headaches in an already complex, expensive implementation?

The Register quotes an evangelist from AWS as saying:

“We will continue to send our contributions and patches upstream to advance these projects.”

DarkCyber interprets this action and Amazon’s explanations from the perspective and context of a high school football coach:

“Front line, listen up, fork that QB. I want that guy put down. Hard. Let’s go.”

Amazon. The best defense is a good offense, right?

The coach shouts:

“Let’s hit those Sheep hard. Arrrgh.”

Stephen E Arnold, March 12, 2019

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