Using caches for stream readers:
When readers read a stream from beginning to end, they become easy to scale.  This is simple strategy and works well for parallelizing computations. However, it introduces latency as streams can be quite long.
A cache served to provide the stream segments do that clients font have to go all the way to the store. It could employ a group of readers that could replenish the segments that are in most demand. There is always the option for clients to reach the store if the cache does not have what it needs. Generally s cache will bring in the segment on behalf of the client if it goes not have it.
The techniques for providing stream segments do not matter to the client and the cache can use any algorithm. The cache also provides the benefits of alleviating load from the stream store without any additional constraints. In fact the cache will also use the same stream reader as the client and with the only difference that there will be fewer stream readers on the stream store than before.
The cache essentially projects portions of the stream so that the entire stream does not have to scanned from begin to end repeatedly. This mode of operation is different from finding popular stream segments across stream readers.
The cache may use a queue to hold contiguous segments from a stream.
The choice of queue is extremely important for peak throughput. The use of a lock free data structure as opposed to an ArrayBlockingQueue can do away with lock contention. The queues work satisfactorily until they are full. Garbage free Async stream readers have the best response time.
The benefits here are similar to LogAppenders except that they are on write path whole these are in read path.
Asynchronous read together with lock free access and skip level access boost performance. The cache may encounter significant size for each segment and a writer that transfers a segment over the network may take time in the order of hundreds of milliseconds. Instead, having a continuous background import for adjustable window of steam segments tremendously improves the load on the stream store while responding to seek requests on segments

This is a continuation of the earlier posts to enumerate funny software engineering practice:

180) Build a product that tries to be ahead of the game in emerging trends and find that a significant legacy from partners still requires older technology integration.
181) Build a product that tries to squeeze different channels into the same stream
182) Build a product that tries to distribute a stream to separate channels when the user is expecting one
183) Build a product that tries to promote a partner application from the same maker to the deteriment of competitors
184) Build a product that tries to emulate open source and invite the world to build with it duing its early stages only to find it shutting doors in its growth stage with bars for acceptance
185) Build a product that does not choose partners to foster growth and find that it cannot sustain innovation by itself
186) Build a product that gives users a tonne of information to go through when they want a summary
187) Build a product to implement a use case and leave it for solution integrators to find bugs
188) Build a product to satisfy some customers only to irk others
189) Build a product with over generalization when some customization would have served neatly
190) Build a product with ambitious charter and find the release timelines reducing the plan.
191) Build a product that does not preserve data between restarts, retries or disaster recovery
192) Build a product that does not retain user settings only to have the user apply them again
193) Build a product by putting together functionality via dependencies and find that the massive surface area attracts all kinds of vulnerabilities.
194) Build a product that creates sdks, command-line clients and other artifacts and find that the versioning for each becomes a maintenance issue.
195) Build a product that does not keep history of all actions, assets and activities only to find significant effort in rebuilding it.
196) Build a product that does not maintain registry for all users and find that there is no blacklist or whitelist capability
197) Build a product that assumes secure comunication via tunnels and find that the tunnels need not be continuous through a proxy.
198) Build a product that does not gain statistics of its usage and find that the pain grows among users
199) Build a product that has no telemetry and not have any insight into how customers are doing with the product.
200) Build a product that has built in dial home capabilities and find that privacy gurus will find it suspect.

This is a continuation of the earlier posts to enumerate funny software engineering practice:

170) Build a product that does not allow users to explore broad or deep without administrator privilege and find users dissatisfied.
171) Build a product that does not allow authoring policies and find that the usage of the product is almost a chaos.
172) Build a product that does not allow differentiation to users either with policies authored by the administrator or out of the box and find that 10% of the users may matter more than the remaining 90%.
173) Build a product that does not let frequent users form their own customizations or dashboards and find that the product is pushed behind those that can.
174) Build a product that does not allow hands off operations with alerts and notifications and find that the product is not up for renewal.
175) Build a product that does not show captivating charts and graphs and the users migrate to applications that do.
176) Build a product that does not allow users to track their activities especially on shared resources and have the administrator be flooded with calls for lost or missing resources.
177) Build a product that does not allow operations to be distributed and have the planners complain about capabilities.
178) Build a product that does not protect data at rest or in transit and have all the watchdogs show up at the door.
179) Build a product that fails to meet the industry compliance and government regulations and find that the product cannot be sold in certain regions.
180) Build a product that tries to be ahead of the game in emerging trends and find that a significant legacy from partners still requires older technology integration.
181) Build a product that tries to squeeze different channels into the same stream
182) Build a product that tries to distribute a stream to separate channels when the user is expecting one
183) Build a product that tries to promote a partner application from the same maker to the deteriment of competitors
184) Build a product that tries to emulate open source and invite the world to build with it duing its early stages only to find it shutting doors in its growth stage with bars for acceptance
185) Build a product that does not choose partners to foster growth and find that it cannot sustain innovation by itself
186) Build a product that gives users a tonne of information to go through when they want a summary
187) Build a product to implement a use case and leave it for solution integrators to find bugs
188) Build a product to satisfy some customers only to irk others
189) Build a product with over generalization when some customization would have served neatly
190) Build a product with ambitious charter and find the release timelines reducing the plan.

Storage products are a veritable data destination for workflows originating outside the product. Their operations generate logs which can also be stored in the same product providing portability, availability and participation in the data plane which comes with guarantees that are typical for data. This immensely improves introspection of the product as various logs, metrics and events can be saved directly in the store itself.  Queries can be written against this introspection data. In particular, Flink can be used with any tier 2 such as Aliyun Object Storage Service or Stream storage. These stores can be treated as append-only data storage with skip-level access introduced for efficient querying.

With the use case of storing the cluster logs within the storage product, let us say we write an FlinkApplication to continuously monitor the number of times there are  delays in accessing the tier 2 storage and the distribution of these delays, analyze the data storage and data access patterns with segments, leverage cache where it helps to avoid accessing data segments directly from the store and finally add additional syntax to segments to facilitate improved performance to queries. 

We propose that segments creation strategies do not affect their augmentation with skip level access. Only a handful of skip-levels with orders of magnitude of 2 is required to speed up access of segments. Back references are not required with as many look ahead segments ensured to be available as the highest skip level for each new segment. Groups of segments may be treated as units for higher level strategies which introduces a secondary layer of segment nomenclature. 

 Stream readers read the stream from beginning to end. The number of readers is allowed to scale arbitrarily because the cost for computation is cheap and it can be parallelized. However, data access and storage performance suffer. When the higher-level semantics of segments are maintained, the techniques for accessing and retrieving segments become irrelevant.  

With the number of readers reduced, the performance of data follows the machine efficiency curve

This is a continuation of the earlier posts to enumerate funny software engineering practice:

160) Build a product where there are no applications without involving external software and dependencies and take a hit when any of them in introduce breaking changes
161) Build a product with many types of overrides and the system administrator is left scratching head on how a policy was violated.
162) Build a product where users find ways to share by bypassing the inbuilt mechanisms such as role based access control.
163) Build a product where loopholes are concealed as methods to bypass policy.
164) Build a product that fails to meet compliance rules and have the administrators deploy third party software to fill the shortcomings
165) Build a product that generates so many notifications to clutter up the users’s screens that they can’t get past easily to do their work.
166) Build a product where the ‘select all’ functionality is missing from resource lists.
167) Build a product where the product is overwhelmingly noisy and have administrators grapple with custom rules to modify the execution
168) Build a product without bells and whistles and find that the product goes unnoticed or worse forgotten.
169) Build a product that can generate beautiful reports only to find that product is used more for reports rather than for data accumulation.
170) Build a product that does not allow users to explore broad or deep without administrator privilege and find users dissatisfied.
171) Build a product that does not allow authoring policies and find that the usage of the product is almost a chaos.
172) Build a product that does not allow differentiation to users either with policies authored by the administrator or out of the box and find that 10% of the users may matter more than the remaining 90%.
173) Build a product that does not let frequent users form their own customizations or dashboards and find that the product is pushed behind those that can.
174) Build a product that does not allow hands off operations with alerts and notifications and find that the product is not up for renewal.
175) Build a product that does not show captivating charts and graphs and the users migrate to applications that do.
176) Build a product that does not allow users to track their activities especially on shared resources and have the administrator be flooded with calls for lost or missing resources.
177) Build a product that does not allow operations to be distributed and have the planners complain about capabilities.
178) Build a product that does not protect data at rest or in transit and have all the watchdogs show up at the door.
179) Build a product that fails to meet the industry compliance and government regulations and find that the product cannot be sold in certain regions.
180) Build a product that tries to be ahead of the game in emerging trends and find that a significant legacy from partners still requires older technology integration.

This is a continuation of the earlier posts to enumerate funny software engineering practice:

150) Build a product that requires non commodity parts and hardware and find that customers are trying to pull apart the product to suit their needs.
151) Build a product that throws arcane errors when the users go off the beaten path
152) Build a product that does not guide the user back to the rails when they go off the beaten path
153) Build a product which has all the necessary ingredients for a successful production deployment but find that the secrets used to operate the software are irreplaceable
154) Build a product which has little or no value in terms of data visualization and find the audience looking for alternatives
155) Build a product in parts where one hand makes one part and another makes a different part and both are not coordinated
156) Build a product where the bug count doesn’t seem to come down and find interesting ideas to hide it
157) Build a product with little or no release gates and see the instability reach the customers.
158) Build a product where the fixes go all the way to the customer on the same day but have it repeated until customers make their mind
159) Build a product with breaking changes in published interfaces and the customers complain.
160) Build a product where there are no applications without involving external software and dependencies and take a hit when any of them in introduce breaking changes
161) Build a product with many types of overrides and the system administrator is left scratching head on how a policy was violated.
162) Build a product where users find ways to share by bypassing the inbuilt mechanisms such as role based access control.
163) Build a product where loopholes are concealed as methods to bypass policy.
164) Build a product that fails to meet compliance rules and have the administrators deploy third party software to fill the shortcomings
165) Build a product that generates so many notifications to clutter up the users’s screens that they can’t get past easily to do their work.
166) Build a product where the ‘select all’ functionality is missing from resource lists.
167) Build a product where the product is overwhelmingly noisy and have administrators grapple with custom rules to modify the execution
168) Build a product without bells and whistles and find that the product goes unnoticed or worse forgotten.
169) Build a product that can generate beautiful reports only to find that product is used more for reports rather than for data accumulation.
170) Build a product that does not allow users to explore broad or deep without administrator privilege and find users dissatisfied.

This is a continuation of the earlier posts to enumerate funny software engineering practice:

140) Build a product where the number bug fixes in frequent patches make the customers roll their eyes.
141) Build a product where the product loses data to corruption or loss from disasters bringing on some of the most petulant customers.
142) Build a product where the product does not fully recover from a disaster.
143) Build a product where the data becomes unavailable to users as the system is brought down or performs some task that prevents it from functioning normally.
144) Build a product and find that deployments are increasing data traffic more than they should.
145) Build a product with specific guidance for deployment and see it put to use in manner different from those suggested
146) Build a product with little or no guidance for the choice of deployment model and find the customer’s gravitate towards the easiest one and then try to scale.
147) Build a product with verbose manual and jargon, and find that customers don’t really want to read that.
148) Build a product like a turnkey solution and find that customers who wanted that in the first place now want to customize it.
149) Build a product with automation packaged via scripts and see its adoption grow astronomically.
150) Build a product that requires non commodity parts and hardware and find that customers are trying to pull apart the product to suit their needs.
151) Build a product that throws arcane errors when the users go off the beaten path
152) Build a product that does not guide the user back to the rails when they go off the beaten path
153) Build a product which has all the necessary ingredients for a successful production deployment but find that the secrets used to operate the software are irreplaceable
154) Build a product which has little or no value in terms of data visualization and find the audience looking for alternatives
155) Build a product in parts where one hand makes one part and another makes a different part and both are not coordinated
156) Build a product where the bug count doesn’t seem to come down and find interesting ideas to hide it
157) Build a product with little or no release gates and see the instability reach the customers.
158) Build a product where the fixes go all the way to the customer on the same day but have it repeated until customers make their mind
159) Build a product with breaking changes in published interfaces and the customers complain.
160) Build a product where there are no applications without involving external software and dependencies and take a hit when any of them in introduce breaking changes